EXTENSION AND THE ADOPTION OF ENVIRONMENTAL TECHNOLOGIES IN THE PARISMINA WATERSHED, COSTA RICA
A Thesis
Presented in Partial Fulfillment of the Requirements for the
Degree Master of Science in the
Graduate School of The Ohio State University
By
Melanie Joy Miller, B.S ******
The Ohio State University
2007
Master's Examination Committee: Approved by:
Dr. David Hansen, Advisor
Dr. William Flinn
Dr. Linda Lobao Rural Sociology Graduate Program Copyright by
Melanie Miller
2007 ABSTRACT
The diffusion of innovations model has been used by social scientists for decades to understand the adoption of new agricultural technologies, but its applicability to environmental as opposed to commercial technologies has been the source of much debate. The “classic” model’s ability to account for the diffusion of environmental innovations is hampered by its productivist and voluntarist assumptions. In addition, adoption patterns have been far more widely studied in North America than in areas such as Latin America. This thesis examines patterns of adoption of a set of environmental farm technologies in the Parismina Watershed in tropical Costa Rica, paying particular attention to the role of a local agronomic university’s extension activities in their dissemination. The findings indicate that overall patterns of adoption remain low; that size of farm is the strongest single predictor of adoption; and that a higher degree of environmental concern and contact with university extension also account for a significantly higher rate of adoption of environmental technologies.
ii ACKNOWLEDGMENTS
As with all major endeavors, this thesis has resulted from the efforts, ideas and
personal support of many different people. I want to thank my advisor, Dr. David
Hansen for all of his support throughout this project. Without his encouragement and
enthusiasm this project would not have been possible. In addition, I wish to thank my
committee members Dr. Linda Lobao and Dr. William Flinn for their continued support
throughout my program.
Special thanks to Matt Mariola for his guidance and advice throughout the Costa
Rica fieldwork and my entire graduate school experience.
I would like to express my gratitude to the faculty, staff and students at EAR TH
University who welcomed me and assisted in this study. A very special thanks to the
EARTH students who worked on this project: Joel Eduardo Reyes Cabrera, Jose
Mauricio Torres Rodriguez, Julian Villca Mallon, Visna Maya Miranda Martinez, Nancy
Huarachi Morejon, and Alex Orlando Gualapuro Gualapuro. Their dedication to the project and commitment to excellence was truly an inspiration. In addition I would also like to thank Herminio Dover for his patience, conversation, and guidance during the fieldwork.
111 Thanks to my family in supporting me throughout all my endeavors. Special thanks to Daniel Foster who lent fresh perspective on a daily basis throughout the writing of this thesis, and to Cristina Santelli who was there for me from day one.
I would like to express my gratitude to my funding sources: the Social
Responsibility Initiative, the Center for Latin American Studies, and the Department of
Energy.
lV VITA
January 9, 1980 ...... Born Rugby, North Dakota
December, 2002 ...... B.S in Agriculture from North Dakota State University
2005 ...... Research Assistant, Costa Rica
2005 - present ...... Research Associate, The Ohio State University
FIELDS OF STUDY
Major Field: Rural Sociology
v TABLE OF CONTENTS
ABSTRACT ...... ii ACKNOWLEDGMENTS ...... iii VITA ...... v LIST OF TABLES ...... ix LIST OF FIGURES ...... x
Chapters:
1. INTRODUCTION AND PURPOSE OF STUDY...... 1
Introduction to the Study ...... 1 Overview of Costa Rica ...... 1 Statement and Significance of Problem ...... 5 Purpose and Objectives of Study ...... 7 Project Objectives ...... 7 Hypotheses ...... 7 Summary ...... 8
2. THE DIFFUSION OF INNOVATIONS ...... 9
The North American Bias ...... 12 The case of conservation technologies and limitations of the classical model.. ... 12 Conservation versus commercial technologies ...... 13 Economic constraints ...... 15 Appropriateness of technology ...... 18 Perception of the problem ...... 19 Knowledge ...... 21 Social factors ...... 22 Non-adoption ...... 23 Conclusions on the Diffusion of Innovations and Conservation Technologies ...... 23 Extension and the Diffusion of Innovations ...... 24 The Beginnings of Agricultural Extension in the Developing World ...... 25 The Green Revolution and Early Extension Practices in Developing Countries ...... 26
Vl Approaches to Extension ...... 27 Conclusions ...... 29
3. EARTH UNIVERSITY PROGRAM OF ECOTECHNOLOGY DISSEMINATION ...... 31
The Parismina Watershed ...... 31 Producer Profiles ...... 34 EARTH University ...... 41 EARTH Extension ...... 43 The Technologies ...... 45 Animals and Crops ...... 46 Biodigestor ...... 4 7 Nutritional Blocks ...... 48 Traditional Compost ...... 48 Worm Compost ...... 49 Effective Microorganisms (EM) ...... 49 Bokashi with EM ...... 50 Forest Species ...... 50 Agro-ecotourism ...... 50 Summary ...... 51
4. Methodology ...... 53
Sampling Procedure ...... 53 Data Collection ...... 54 The Sample ...... 54 Pre-survey Preparation ...... 54 Survey Instrument ...... 55 Interviewers ...... 56 General Model and Hypotheses ...... 56 Measurement of Variables ...... 59 Statistical Test of Model and Hypotheses ...... 65 Correlation Analysis ...... 65 Multiple Regression ...... 66 Chi Square Analyses ...... 67 Summary ...... 68
5. RESULTS AND DISCUSSION ...... 70
Frequency Distribution of Variables in the Model ...... 70 Descriptive Statistics ...... 70 Land Tenure ...... 72 Contact with EARTH University ...... 74
Vll Concern for the Environment ...... 7 5 Adoption of Eco-technologies ...... 76 Test of Hypotheses in Model ...... 77 Relative Importance of Variables in the Model...... 79 Impact of EARTH Contact on Adoption of Eco-technologies ...... 81 Residence in EARTH Contact Community ...... 81 EARTH Extension Activities and Environmental Technology Adoption 85 Summary ...... 87
6. SUMARRY AND CONCLUSIONS ...... 89
Summary ...... 89 Test of Model ...... 91 Study Limitations ...... 94 Further Research ...... 95
LIST OF REFERENCES ...... 97 APPENDIX ...... 103
Vlll LIST OF TABLES
4.1 Inter-item Correlation Matrix of Environmental Concern ...... 60 4.2 Education Frequencies and Index Scores ...... 61 4.3 Income Frequencies and Index Scores ...... 62 4.4 Inter-item Correlation Matrix of Socioeconomic Status ...... 62 5.1 Descriptive Statistics of Respondents ...... 71 5.2 Education of Respondents ...... 72 5.3 Land Tenure Characteristics ...... 73 5.4 EARTH Contact Frequencies ...... 74 5.5 Environmental Attitudes Index ...... 75 5.6 Number of Technologies Currently in Use ...... 76 5.7 Correlation Matrix for Variables in Traditional Diffusion-Adoption Model ...... 78 5.8 OLS Regression of Technologies Adopted on Gender, SES, EAR TH Influence, Concern for Environment, and Hectares Cultivated ..... 79 5.9 Number of Ecotechnologies Adopted in Communities With and Without Direct Participation by EARTH University ...... 82 5.10 Primary Source oflnformation Listed by Ecotechnology Adopters .... 84 5.11 EARTH Extension Activities and Adoption of One or More Environmental Technologies ...... 85
lX LIST OF FIGURES
Figure
4.1 The General Model ...... 57
x CHAPTER 1
INTRODUCTION AND PURPOSE OF STUDY
Introduction to the Study
This study exammes patterns of adoption of a set of environmental farm
technologies in the Parismina Watershed in tropical Costa Rica, paymg particular
attention to the role of a local agricultural university's extension activities m their
dissemination.
Overview of Costa Rica
Costa Rica is a small country. It is about the size of West Virginia, and has a population of roughly four million (World Fact Book, 2007). Located in Central
America, it is bordered by Nicaragua to the north and Panama to the south. Costa Rica has been viewed as exceptional among Latin American countries. On a continent that has been marred by dictatorship, civil war, poverty, deforestation and a host of other serious problems, Costa Rica stands out as an oasis of peace and stability. As the oldest democracy in Latin America, it has an international reputation for its peace and ecological initiatives. It has a stable economy, relatively equitable land distribution, and a sizable middle class (Cooke, 2005).
1 The United Nations Human Development Report for 2006 ranks Costa Rica 48th
out of 177 countries based on life expectancy, education, and income (United Nations,
2006). According to this index, Costa Rica is far ahead of its neighbors (in comparison,
Nicaragua ranks I 12th). Costa Rica has a comparatively educated population, having a
literacy rate of 95 percent which is the highest in Latin America. The life expectancy in
Costa Rica is 78 years, which is also the highest in Latin America and comparable to
highly industrialized countries. It is due to government spending on clean water,
nutrition initiatives, health education, and a health insurance program (Cooke, 2005).
Its relatively stable economy is largely dependent on agriculture, tourism and
electronics exports (World Fact Book, 2007). An Intel microprocessor plant opened in
1998, and by 2004 high-technology exports constituted 3 7 per cent of manufactured
exports and over two-thirds of all exports (United Nations, 2006). Foreign investors
continue to be attracted to Costa Rica due to the highly educated labor force and the relative peace and stability found there. These same traits also lend themselves to the tourism industry, as does Costa Rica's reputation for natural beauty and ecological diversity. Tourism became the largest source of foreign exchange in 1994, after twenty years in third place behind coffee and banana sectors (Cooke, 2005). It continues to gain momentum, with 1.6 million tourists visiting the country in 2005 (World Tourism
Organization, 2006).
With all of these positive characteristics, it is easy to accept Costa Rica as an anomaly amongst its Latin American counterparts. By shifting the lens slightly, it is evident that Costa Rica is also affected by a host of important problems and issues, many
2 of which are shared with their neighbors. Thus it is incorrect to simply accept Costa Rica
as an outlier and to dismiss its relevance for understanding patterns of development that
may lead to insight in Latin America and beyond (Palmer and Molina, 2004).
For example, Costa Rica experienced a large influx of Nicaraguans in the 1980s
due to the conflicts taking place at that time. Despite the influx, the Costa Rica economy
was able to expand to fit the sudden growth in the mainly unskilled labor force, and the
unemployment rate remained fairly stable (World Fact Book, 2007). Many Nicaraguans
remain in the country, attracted by jobs and a higher standard of living. The presence of
these migrants has put a strain on many of the social services, has become a source of
ethnic tension between the two groups.
While Costa Rica has a reputation for natural beauty and ecological diversity, it
experiences a variety of environmental challenges. For example, during the 1980s Costa
Rica had one of the highest deforestation rates in the world (Camino et. al, 2000). From
1979 and 1992 nearly one million hectares of natural and secondary forest were deforested, with the majority of it converted to pasture (Camino et. al, 2000).
Deforestation was a symptom of unsustainable land use policy that persisted for decades.
Most of the cleared land was used for cattle grazing and agriculture. Until recently, squatters were allowed to move onto a piece of land and gain certain rights to it by clearing it.
While Costa Rica has been heralded as the original "banana republic", its long history with the banana industry has been credited with coastal water pollution, as well as soil erosion and degradation (World Fact Book, 2007; Estado de la Nacion, 2004). The
3 recent rapid growth in the pineapple sector has led to an increasing level of concern over
soil erosion and water contamination.
The study site itself is characterized by many of these problems. The Parismina
Watershed (situated in the province of Limon) is home to several banana and pineapple
plantations, with the small farmers filling in around the fringe on the most marginal land.
The watershed is part of an area that was most recently cleared for agriculture, and has
been named the "last frontier" (Programa Estado de la Nacion, 1997). From 1979 to
1992, the province of Limon experienced a loss of 128,000 hectares of natural forest,
with much of the deforested land converted into pasture and crop land (Camino et. al,
2000). In addition, the area has recently experienced an increase in the production of
pineapple, which is known to cause reduced water quality, pest problems, and soil
degradation. Overall, the rapid change in land use has contributed significantly to the
deterioration of the quality of environment in the area. The Food and Agriculture
Organization (F AO) has categorized soil degradation in the province as "very severe".
The agricultural potential in tropical regions is often unsustainable because the production capacity of the land is rapidly exhausted after deforestation due to nutrient leaching and soil erosion (Weinberg, 1991 ). These problems are exacerbated by the demand for food in these often impoverished areas (National Research Council, 1993).
Long term sustainability is not a priority for the small farmer whose immediate concerns are providing food for the family and assuring quality of life in the short-term (Eswaran,
Virmani and Spivey, 1993 ). Many of the small producers in the Parismina Watershed
4 experience these same problems, many of these are resource poor and find themselves
continually experiencing low yields.
Some institutions, such as the Escue/a Regional de las Tr6picos Humedos
(EARTH University), in Guacimo, Costa Rica, have taken up the challenge to find
sustainable solutions that balance agricultural production and environmental preservation.
Through research at EAR TH, new technologies and conservation practices continue to be
developed to help farmers in the humid tropics improve their quality of life and preserve
the delicate environment in which they live. In addition to a strong science orientation,
EAR TH has an active extension component. Both faculty members and students work in
neighboring communities to disseminate information among farmer groups, various
organizations, and schools.
Statement and Significance of Problem
Within disciplines such as agricultural and ecological engineering, there has been
a longstanding interest in designing farm technologies or practices that are more
environmentally friendly. Once these technologies or practices are developed, the task of disseminating information and inducing adoption still remains. The social sciences - particularly rural sociology - have developed a large body of research on the adoption of innovations.
Since the 1970s, the adoption-diffusion literature has featured a specific dimension focused on the adoption of environmental innovations, usually among farmers.
A growing body of research investigates this theme in developing countries, but most of
5 it has been carried out in North American locations. In addition to introducing a
generalization problem owing to location-specific assumptions (Holden, 1972), this
North American bias is unfortunate because some of the most pressing agro
environmental problems are located in the developing world, including sensitive areas
such as the humid tropics.
In particular, the adoption of conservation technologies and practices is poorly
documented in Latin America (Vera, 2001). Previous studies demonstrate that small
holder farmers are aware of the environmental problems that result from the use of
pesticides and other unsustainable agricultural practices (Agne and Waible, 1997).
However, resource poor farmers are often unwilling or unable to adopt a new technology
due to the financial risk involved (Geertz, 1963; Holden, 1972). Other important factors
that are known to play into adoption of conservation technologies include the perception
nature and severity of the environmental problems, the perception of profitability of any
given agricultural innovation, and the amount and quality of information available to the
producer (Vanclay and Lawrence, 1994; Saltiel et al, 1994; Nowak, 1987). An increased rate in adoption of environmental technologies may be achieved if additional barriers to adoption are identified.
Little research has been done on conservation technologies in the context of Latin
America. In fact, there is little understanding of how small holder farmers in this context perceive their environment. A considerable body of research has established that when farmers perceive an environmental problem, they are more likely to adopt innovations that aid in the management of those problems (Vanclay and Lawrence, 1994). However,
6 little research regarding environmental concern has been carried out among small
producers in the Latin American context. This is an important issue to address because
the perception of an environmental problem is very complex and involves many factors.
Little research has been carried out on how concern for the environment translates into
adoption of environmental technologies in Latin America.
Purpose and Objectives of Study
The present case study was designed to investigate the relationship between
EARTH University extension activities in the rates of adoption of a set of conservation
technologies which they promote. It focuses on the adoption, rejection and
discontinuation rates of these technologies, as well as a clearer picture of communication
networks that are already in place in the community. Environmental attitudes will be
assessed in order to discern if greater environmental concern translates into higher rates
of adoption.
Project Objectives
• To identify factors related to the adoption of conservation technologies and
practices.
• To determine the relative importance of other extension organizations versus
EARTH extension contact in the diffusion process.
Hypotheses
• Socioeconomic status as measured by income and level of education is positively
related to adoption of conservation technologies and practices.
7 • Fann size is positively related to adoption of conservation technologies.
• Gender and age are positively related to the adoption of conservation
technologies.
• Living in a community with current EARTH induced contact is positively related
to the adoption of conservation technologies and practices.
• EAR TH University is an important disseminator of information of conservation
technologies in the watershed.
• There are significant differences in technology adoption due to the nature of
contact that respondents have with EAR TH University.
• EAR TH has more success at promoting certain conservation technologies.
• Greater concern for the environment is positively related to the adoption of
conservation technologies.
Summary
Costa Rica is a dynamic tropical country that faces many environmental challenges. Recent land use changes have presented additional environmental problems, particularly in the study area. Little is known about the perception of these environmental problems by small holders in the area, and about the adoption of conservation technologies in a Latin American context. This study will shed light on these topics through empirical field work. It is a case study of the diffusion and adoption of conservation technologies in Parismina Watershed.
8 CHAPTER2
THE DIFFUSION OF INNOVATIONS
The literature on the diffusion of innovations is extraordinarily extensive and
complex, having occupied a prominent place within the discipline of rural sociology for
consecutive decades, and more recently being taken up by other fields including
geography and economics (Rogers, 2003). Rural sociologists have tended to favor the
innovation-diffusion model made popular by Everett Rogers, in which the diffusion of
innovations is explained as the spread of some new product, idea, or behavior over time
through a social system (Rogers, 2003). Typical diffusion studies cover topics such as
how technical innovations are diffused in a social system, what the characteristics of the adopters are, and the role of interpersonal networks and other communication channels in determining rates of adoption (Rogers, 2003 ).
Innovation-diffusion research can best be understood by examining its origins.
This type of research was first undertaken to address specific agricultural issues. This has affected the diffusion model and the limitations that have come to be recognized in diffusion research. Diffusion research became popular in the 1940s, just as many new agricultural technologies were being introduced to farmers. As there was a backlog of agricultural innovations, there was much concern about these technologies being adopted
9 quickly by producers. Questions arose about producers' willingness to change their
fanning practices and how the adoption process could be expedited (Van Es, 1983 ).
Although diffusion studies had taken place previously, the 1943 Ryan and Gross
hybrid com study started an important research agenda in rural sociology (Ruttan, 1996).
This study served as an "academic template" for classical diffusion research that persisted
until the 1970s (Ruttan, 1996), with a focus on the linear socio-psychological factors that
are related to adoption (Fliegel, 2001). With this approach, rural sociologists focused on
farmers' adoption behavior, the various information flows to the farmer, and the
individual farmer characteristics related to adoption (Fliegel, 2001 ). Even with this
limited research design, the model has been tremendously successful in predicting the
adoption of a wide array of agricultural technologies in the United States (Nowak, 1983 ).
In these early years of research that followed the classical model, the slow
response of farmers was seen as a problem. Research focused on identifying the factors
that would slow adoption such as lack of information, the inability to translate information into action, and unwillingness to adopt. In those studies, rural sociologists tried to determine if the antecedents of adoption of a given innovation were the same as the antecedents to adopt other innovations (Fliegel, 2001). Later research then focused on whether the farmer's adoption of one innovation could serve to predict that farmer's behavior with respect to other innovations (Fliegel, 2001 ). Both of these approaches concentrated on the farmer's individual characteristics, and heavily influenced the development of the classical diffusion model. The main idea behind this model was that a farmer's decision to adopt any given innovation was a voluntary act. Later, this
10 assumption of voluntary action would be called into question with regard to certain types
of technologies. However, it is important to understand the history of the classical model
and diffusion research to fully conceptualize the original assumptions upon which the
model rests.
In the 1950s there was a proliferation of studies using this classical model. In the
1960s there was an expansion of diffusion research to the developing world, and the
1970s marked the beginning of a period of criticism for diffusion research (Rogers,
2003). From the 1970s forward, many of the assumptions that the model relies on were
challenged, and certain applications of the model were called into question. Much of this
criticism came from within the discipline of rural sociology (Ruttan, 1996). Several
uncertainties were brought forward, including the model's ability to explain the diffusion
of conservation practices and technologies and the applicability of the model to the
developing world. These debates raged in the 1970s and 1980s, and the basic points
made by the model's critics during this period continue to be drawn from today.
The quantity of diffusion research declined in the 1980s and it plays a lesser role
than it had previously. Rogers (2003) argued that this decline in diffusion research can be attributed to the fact that most of the major research problems related to the model had been solved. He believed that the drop in numbers of studies was not due to the inadequacy of the model itself. Ruttan (1996) noted that many rural sociologists turned away from the diffusion model in order to address other important research needs, and also because technological change in farming communities began to be viewed as a source of inequity and as destructive of rural communities. This decline of diffusion
11 studies in rural sociology coincided with the upswing of diffusion studies in economics
(Ruttan, 1996).
The North American Bias
When the diffusion model is transferred to the developing world, many of the
assumptions of the model do not hold up (Holden, 1972). At the outset of the debate,
(Bordenave, 1976) and still more recently, (Rogers, 2003), scholars reminded us that the
classical diffusion model was created in a substantially different socio-cultural context
than that found in countries in the developing world. They argued that great care must be
taken when transferring the adoption model to a less developed country. Agricultural
production in the third world is often marked by a lack of the same technical
infrastructure and state support that many North American and European countries take
for granted. Access to land, markets, and legal protection are not nearly as commonplace
or easy to obtain for developing country peasants (Fliegel and van Es, 1983).
Furthermore, information channels may vary greatly, the innovation may challenge the norms of the society, and subsistence farming simply presents a different market climate not necessarily conducive to the development or spread of productivity-enhancing technologies or practices (Holden, 1972).
The case of conservation technologies and limitations of the classical model
The above historical analysis of the model shows that early diffusion research placed a heavy emphasis on certain types of technologies, which had allowed the model
12 to rest on certain assumptions. The case of conservation technologies is very different
because some of those assumptions may be seen to be false, which limits the model's
ability to contribute to the discussion on conservation technologies.
This section of the paper will highlight some of these issues regarding the
traditional innovation-diffusion model and its applicability to conservation technologies.
Conservation versus commercial technologies
Farmers are faced with a bewildering array of agricultural technologies from
which to choose. One of the main contradictions in these technologies is that some are
designed to increase production with little regard for environmental conservation, and
other technologies focus on environmental conservation with little concern about
increased production (Heffernan, 1984). There has been some debate in the literature
over the generalizability of the classical diffusion model's ability to explain adoption of
different types of innovations. It has been argued that a universal theory is not
appropriate because of the fundamental differences between different types of
innovations (Downs and Mohr, 1976).
Agricultural innovations can be divided into two main classes: environmental and
commercial (Pampel and van Es, 1977). Vanclay and Lawrence (1994) describe a commercial innovation as an innovation that has been developed for commercial reasons.
The choice of non-adoption affects no one other than the adopting farmer, and adoption is in the farmers' self interest. Thus, it is assumed that adoption will eventually occur
(Vanclay and Lawrence, 1994). The classical diffusion model has been tremendously successful in predicting adoption of commercial technologies. This is because the model
13 was developed during a time when many commercial innovations were being diffused.
Many rural sociologists used and developed the model based on the concept of voluntary
adoption of commercial technologies.
Environmental innovations are described as the use of techniques, methods and
approaches to improve land management rather than to increase farm productivity
(Vanclay and Lawrence, 1994). Often with environmental innovations, the costs of
adoption are borne by the individual farmer, and the benefits are mainly social. Often,
such adoption is not in the farmer's economic interest, and the result is usually large
scale non-adoption (Van clay and Lawrence, 1994 ). Environmental innovations were not
generally studied until after the model had been in use for several decades. By this time,
the model was fairly developed and rested on assumptions that only applied to
commercial innovations. The issue of environmental innovations challenges several
aspects of the model, including the assumption of voluntary adoption. Fundamental
differences can be seen between reasons for the adoption of environmental innovations and commercial innovations.
The issue of differences between types of innovations becomes more complex when related to the idea of innovativeness and other personal characteristics that are the focus of the classical model. Pampel and van Es ( 1977) note that "farmers appear to be innovative either with respect to commercial practices or with respect to environmental practices, but not both" (p. 67). They also claim that commercial innovations are simply easier to predict using the classical model. That is, a regression analysis using a standard set of independent variables (farm size, income, age, etc.) explains a much higher portion
14 of the variation m adoption of the commercial innovations than of environmental
innovations, which are left largely unexplained. Interestingly, they found that the single
strongest predictor of environmental innovations is farmers' age which is not a significant
predictor of commercial innovations. Age has a positive relationship to adoption of
environmental innovations, but an insignificant relationship to commercial innovations.
The authors close by cautioning against the use of the traditional adoption model to
explain the adoption of environmental innovations. In the past, these traditional
assumptions have been used to justify a voluntary approach to environmental practices,
but the empirical ground on which to base this justification may be quite thin.
Vanclay and Lawrence (1994) claim that the conflict between environmental and
commercial innovations is not always present. At times, conservation technologies may
be adopted for commercial reasons such as labor and energy savings, as well as cost
effectiveness, rather than for environmental benefits (Vanclay and Lawrence, 1994).
While environmental benefits do take place regardless of the motivation for adoption, this type of adoption does not ensure that these benefits will be maximized (Vanclay and
Lawrence, 1994).
Economic constraints
This leads to a second critique of the classical model, which revolves about the economic constraints related to the adoption of new technologies. As noted previously, much diffusion research has been based on scientific, reductionist values oriented to profit (Frank, 1992a). When evaluating a new agricultural technology this vital issue to needs to be considered. According to the classical model, farmers will be reluctant to
15 adopt any new innovation unless they view it as profitable to their farming operation.
Profitability is not an objective fact, but a perception on the part of the farmer that may
vary with the farmer's scale, style of farming, and ecological context. What is important
is not the "true" economic profitability of an innovation, but a farmer's perception of its
profitability (Saltiel et al, 1994). Therefore, economic issues related to the adoption of an
environmental technology are very complex and are subject to many different factors.
When faced with financial stress sufficient to cause a change in farming practices,
the first move for many economically stressed farmers is to reduce their adoption of new
technology in order to reduce costs and to maximize short run output (Swanson et al,
1986). In fact, during periods of economic stress, farmers often ignore new conservation
practices and discontinue current conservation practices if they are not seen to contribute
to short-run profits (Swanson et al, 1986). Only if the financial stress continues after the
cost reduction strategy fails will they begin to consider the adoption of alternative
technologies (Frank, l 995a, 1995b ). It is only at this point that some farmers may adopt more "ecological" practices, such as substituting internally generated fertilizers for synthetic ones in order to increase liquid assets (Vera, 2001).
As mentioned above, short-term survival of the farm takes precedence in times of economic stress while long-term environmental conservation becomes a lesser priority
(Swanson et al, 1986). "The ratio between short term and long term benefits will also affect the decision to adopt, with the adoption of practices having a higher ratio of short term benefits taking precedence over practices having only long term benefits" (Vanclay and Lawrence, 1992). However, there is some debate about whether environmental
16 innovations provide any economic benefit to the farmer (Quiggin, 1987; Fleigel and van
Es, 1983). It is safe to say that economic benefit from environmental innovations is
unclear, and that if farmers were to base their adoption decision solely on economic
criteria, little adoption of environmental innovations would take place (Vanclay and
Lawrence, 1992). Fortunately, farmers utilize a variety of criteria during the decision
making process and are not strictly rational (Vanclay, 1992).
In addition to the economics of the innovation, another important issue to
consider is financial flexibility. Some farmers have the financial flexibility to implement
new changes that may cost money and carry with them a certain amount of financial risk.
Considerable capital outlay is often required when adopting a new technology, and the
farmer may have to forgo income until the new innovation produces an income (Vanclay
and Lawrence, 1994). Many farmers in non-North American or European countries are
subsistence or near subsistence farmers. If markets exist for their products, they are
likely to be oversaturated with products. Thus, the financial situation facing such farmers
is volatile and not conducive to taking risks (Holden, 1972). Even when the economic reasons to adopt are clear, many marginal farmers simply do not have the financial
flexibility to adopt new technologies (Geertz, 1963 ).
Economic considerations are undoubtedly very important to understanding technology adoption, mainly because most resource conservation options are viewed as nonproductive expenditures by farmers (van Es, 1983). Even if long-term benefits exist, such as those provided by conservation programs, the short term farm budget still needs to be take into consideration (van Es, 1983). This is because individual farmers cannot
17 pass on additional costs to the consumers. Therefore, the additional costs of a
conservation technology must be absorbed by the farm-firm (van Es, 1983). In sum, the
economic questions that arise with conservation technologies in agriculture are found to
be extremely complex and deviate from the economic pattern of other agricultural
technologies. The classical diffusion model fails to address adequately the economic
complexities concerning conservation technologies.
Appropriateness of technology
A third critique pertains to the bias towards any given innovation. The pro
innovation bias is a serious shortcoming in diffusion research because it implies that an
innovation should be diffused and adopted by all members of a social system (Rogers,
2003). The general idea of innovation is a positive notion associated with improvement
(Down and Mohr, 1976; Rogers, 2003 ). Since many of the innovations that are studied,
especially in agriculture, augment productivity and thus profitability, many studies fall
victim to this assumption. These values infer that technological innovations are
desirable, suitable for adoption, and directly applicable to the personal environment of the target audience (Frank, 1995a). While the pro-innovation bias is latent and largely unintentional, it is still a limiting factor of diffusion research (Rogers, 2003).
New technologies, including conservation technologies, are not universally applicable. Each farm, based on its environmental situation, will need to employ appropriate environmental management strategies (Vanclay and Lawrence, 1994). It simply doesn't make sense to analyze a farmer's conservation behavior without first analyzing their conservation needs. Conservation practices cannot be grouped together
18 and generalizations made about their profitability (Heffernan, 1984). The farming system
as well as soil type, topographic conditions, and climate are just a few of the factors that
need to be taken into consideration (Nowak and Korsching, 1983; Heffernan, 1984). In
addition, type of farm enterprise, farm size, land tenure and planning horizon have been
found to influence adoption (see Buttel, 1990). A farmer takes a diverse array of factors
related to their farming environment into consideration when evaluating a new
technology.
The personal and farm objectives that farmers hold are very important
considerations when discussing the appropriateness of any given technology. V anclay
and Lawrence (1994) note that farmers are more likely to adopt innovations that are
compatible with other farm and personal objectives. They also point out that new and
often complex innovations represent major changes in the management of the farm, and
may not be compatible with other farm operations. Because of the nature of the family
farm, farmers take into consideration their personal capital needs, such as household
expenditures and education of their children, as well as their farm-firm needs.
Environmental technologies tend to be associated with fundamental changes to current agricultural practices. Therefore, most environmental innovations are deemed to be not compatible with current farm management practices or farm and personal goals (V anclay and Lawrence, 1994).
Perception of the problem
Rogers (2003) notes that the adoption process often begins with the recognition of a problem or need. If water quality, soil erosion and other environmental concerns are not
19 defined to be urgent problems by farmers, they will not attempt to fix them (Nowak and
Korsching, 1983 ). While farmers have often been viewed as "the problem" within the
environmental movement (Heffernan, 1984), they cannot be expected to adopt
technologies that they perceive to be less profitable and more inefficient in order to fix
problems that they do not recognize. In short, farmers may view environmentally friendly
practices as solutions to non-existent problems (Nowak and Korsching, 1983).
Much research has established that when farmers perceive an environmental
problem, they are more likely to adopt innovations that aid in the management of it
(Vanclay and Lawrence, 1994). As Nowak (1983) points out, perception of an
environmental problem is complex because producers tend to evaluate the environment
themselves. They often underestimate their own environmental problems, even if they
acknowledge that there are serious environmental problems at the national, state, and
community levels. Farmers may even think that their neighbors may have a serious
environmental problem, but the problem is not present on their own farm.
Education efforts have often been counterproductive as a means to help farmers identify their environmental problems (Nowak, 1983). In the case of soil erosion, extension efforts often utilize dramatic pictures of the Dust Bowl, exposed tree roots, and other extreme examples of erosion, that farmers do not see taking place on their own farms (Vanclay and Lawrence, 1994). They believe that they do not have a problem because they do not see the same type of extreme degradation taking place on their own farm (Nowak, 1983). When farmers do acknowledge the problem on their own farm,
20 they often develop a fatalistic attitude, rather than changing their management practices
(Vanclay and Lawrence, 1994).
Knowledge
There is also the issue of knowledge with regards to a new technology. Access to
knowledge about a new technology affects adoption, in addition to knowledge about the
environmental problem itself (Saltiel et al, 1994). Both Saltiel et.al. (1994) and Nowak
( 1987) surmised that the role of information is to help reduce perceived risk on the part of
farmers. New technology usually brings with it debate about its applicability and
effectiveness (V anclay and Lawrence, 1994 ).
In most cases in North America, information concemmg new innovations is
widely available, easily obtainable, trustworthy, and easily decipherable. This is not the
case in underdeveloped countries according to Holden (1972). In less developed
countries there may be only one channel of information, and this channel may be
unreliable, or perceived as unreliable by local producers (Holden, 1972).
Furthermore, in either context, awareness and knowledge do not always lend themselves to eventual adoption. Particularly with environmental innovations, farmers may be aware and knowledgeable about environmental problems and their solutions, but fail to adopt because of other factors affecting the decision making process (Vanclay and
Lawrence, 1994). The classical model assumes that farmers seek new technology to solve their problems, when in fact this may not be the case. In addition, farmers may have knowledge about a new technology, but adoption may not occur because the technology may not be appropriate for their needs as discussed above.
21 Social factors
Aside from economic and environmental considerations, farmers are constrained
by other structural factors. For example, the socio-behavioral context of the adoption
environment must be taken into consideration. Most farmers give great importance to
local norms that defines a "good farmer" (Heffernan, 1984 ). Social acceptance of an
innovation by neighbors has been categorized as an additional benefit to the adoption of
an innovation (Frank, 1995a), but the lack of acceptance can just as easily serve as a
deterrent until openness to a given technology achieves a critical mass among a local
group of farmers. "Except for a small number of maverick innovators, most farmers
would not want to be the only one to undertake a new practice, or grow a new crop"
(Vanclay and Lawrence, 1994).
People are naturally cautious when approached with a new idea or technology.
However, less risk is associated with it when potential adopters become familiar with it.
Familiarity with the outcome of an innovation is often acquired by observing other actors in a network (Wejnert, 2002). Because farmers often rely on other farmers for information, the "social infrastructure" must be in place until there is sufficient interest in an innovation for there to be wide spread adoption among farmers in a particular area
(Vanclay and Lawrence, 1994). Leaming through observation of other farmers in the local area lowers the risk associated with a new innovation, and this social aspect can influence the rate of adoption.
22 Non-adoption
This debate has culminated in recent years with a handful of articles that
essentially sum up the debate with a single, fundamental point: the non-adoption of any
given technology, far from being a case of laggardness or antiquarianism as previously
insinuated, is a rational act on the part of a farmer given the informational,
socioeconomic, and environmental context in which he/she finds his/herself.
"Individuals assess the utility of new practices by relating their perception of the practice
to their experience, and interpreting the value of that practice to their needs at a particular
place and time" (Frank 1995a: 292).
Those not seeking out new innovations may simply not feel economic pressure or
perceive environmental problems. They are satisfied with their situation and have good
reasons for deciding to not adopt (Frank, 1995b ). Especially in the case of conservation
technologies, when the advantage of a given innovation is not apparent, the farmer's
decision to not adopt is an active and rational act (Frank, 1995a).
Conclusions on the Diffusion of Innovations and Conservation Technologies
The above analysis has considered the North American bias found in diffusion literature, as well as many of the shortcomings of the classical diffusion model when applied to conservation technologies. The model is better suited to commercial technologies, which assumes voluntary adoption and private benefits. Because of the historical context in which the model was developed, the classical model inadequately accounts for the adoption of conservation technologies as an entire class of technologies.
Secondly, economic issues surrounding the adoption of conservation technologies are
23 complex because of varied perceptions of profitability and the fact that farmers rarely
profit or perceive a profit from voluntary adoption of these technologies. In addition, the
appropriateness of a technology for a given farming system and ecological environment
needs to be considered. The pro-innovation bias that has pervaded the innovation
diffusion tradition has not adequately prepared researchers to address these issues. Also,
perception of an environmental problem and the knowledge of technology to solve it
assume that farmers are seeking new technology to solve their problems, while that may
not be the case. Finally, the classical model has defined the term non-adopters in a
negative light, when actually their reasons for non-adoption may be quite valid. It is for
all of these reasons that the classical diffusion model and the assumptions upon which it
is based have been called into question.
Extension and the Diffusion of Innovations
While the adoption model was being critiqued within academia, a parallel critique
was confronting the more applied world of agricultural extension. Extension and the traditional adoption/diffusion model have both been based on the assumptions that technological innovations are inherently desirable and that all eligible individuals will eventually adopt them. The model also assumes that adoption is largely a voluntary phenomenon whose calculation need not incorporate social structural variables. These assumptions have been called into question during the last two decades.
Criticism of the application of diffusion of innovations to international development has also risen to the forefront of the literature. In order to effectively foster
24 innovation adoption, questions remain concerning what knowledge to communicate, how
it should be communicated, and who it should be communicated to. Extension efforts in
developing countries appear to have addressed these questions through a process of trial
and error. Worldwide, the institution of agricultural extension is increasingly called into
doubt (Roling, 1995). Vanclay and Lawrence (1994) assent that the entire extension
apparatus, is in a state of multiple crises: dwindling financial support, an apparent loss of
relevance to farmers, and, most notable in the present case, limited success at fostering
the adoption of environmental technologies.
The Beginnings of Agricultural Extension in the Developing World
After World War II, the United States was a leading supporter of agricultural
development in developing countries, and exported its agricultural extension model to
those countries (Rogers, 1989). Extension programs in these developing nations were
often non-existent or severely lacking in funds. More importantly, they were often not
effectively connected with the local agricultural universities (Rogers, 1989). The result
was that the agricultural system experienced contact with local farmers, but results of
these contacts were not influencing researchers (Rogers, 1989). Historically, the
extension service served a vital role in the transmission of agricultural innovations to producers, but also provided a mechanism for feedback to researchers (Umali and
Schwartz, 1994). This feedback to researchers was largely missing in the developing world, and in combination with a lack of inadequate farmer contact, was found to be relatively ineffective.
25 Similarly, the United States agricultural extension model, which had been
relatively successful in the United States, was found to be only partially transferable to
different contexts (Rogers, 1989). Without modification, the extension model was not
successfully transferred to the developing world, thus forming the root of many of the
agricultural development issues that later occurred.
The Green Revolution and Early Extension Practices in Developing Countries
Beginning with the Green Revolution, agricultural extension was inspired by the
classical diffusion of innovations model. It was rooted in a paradigm that emphasized
linear technology transfer and the increase of production. During the Green Revolution,
diffusion of innovations research was prevalent in the literature, as social scientists
worked to uncover barriers to adoption in order that the diffusion of innovations could
occur as efficiently and quickly as possible (Van Es, 1983). Indeed, dramatic changes in
production did occur through increased yields and greater income of farmers (IFPRI).
However, the rapid diffusion of innovations in the context of the Green Revolution was not without criticism, particularly in the developing world.
A large body of literature that addresses the impacts on the developing world resulting from extension efforts adopted during the Green Revolution exists. Impacts included changes in cropping patterns, agricultural productivity, the structure of class relations, and food self-sufficiency (Das, 2000). Adoption of new technologies and practices occurred mainly in favorable production environments that had ready access to markets, meaning that adoption did not occur uniformly, and bypassed many areas in the
"first generation" of technological change (Norman and Matlon, 2000).
26 In addition, concerns regarding the equality of the diffusion process were brought
forward. Critics argued that large producers were the main adopters of the new
technologies, while small and relatively resource-poor farmers were met with a variety of
barriers including access to credit, infrastructure limitations and knowledge of the new
technologies (Rogers, 2003). The diffusion of new innovations was actually seen to
increase inequality in some cases, thus puzzling diffusion researchers and challenging the
classical model.
As the focus of worldwide agriculture shifted from simply increasing yields to
sustainability and environmental compatibility, the traditional assumptions of the model
again were challenged. Up until this point, classical diffusion of innovations model
tended to focus on the adoption of individual technologies. A holistic approach that
considers the complete farming system was not prevalent, with an incrementalist, "add
on" approach being favored (V anclay and Lawrence, 1994). Rather than the incremental
adoption of "add-on" commercial innovations, environmental technology adoption is
typically part of a larger suite of activities often referred to as whole farm planning. It is more of a cumulative process than simply the adoption of a given innovation (Roling,
1995). So an extension apparatus, which approaches dissemination of environmental innovations in the same way as commercial innovations, will achieve only limited success.
Approaches to Extension
The classical diffusion model initially fostered a linear approach to the diffusion of innovations in which researchers generate knowledge which extension workers convey
27 to producers (Roling, 1995). This approach generally provides technologies in a "one
size fits all" fashion, with little regard for the non-technical factors that affect the
adoption of innovations (Davidson and Ahmad, 2003; Adhikarya, 1996). In addition, the
lack of a feedback loop tends to only consider innovations generated by research
institutions, largely ignoring innovations developed on-farm (Davidson and Ahmad,
2003). This approach has been largely discarded throughout the world and is widely
regarded today as "nai:Ve and counterproductive" (Davidson and Ahmad, 2003; p. 23).
Eventually, a more participatory approach to agricultural extension emerged in the
United States as well as the developing world. The power structure of partnerships
among development agencies, experts and farmers were addressed, leading to
fundamental changes in the system. Through this participatory approach, a new
innovation came to be viewed not simply as a new technology delivered to a target group,
but rather as a new practice developed through exchanges of information among
stakeholders (Norman and Matlon, 2000). The fundamental reasoning behind this was that researchers could work directly with farmers to address their specific concerns.
Farmers were seen more as partners who posses valued knowledge (Buhler et. al, 2002).
The participatory approach allowed new innovations to be continually and more easily adapted to new contexts and needs, and guides research through a stronger feedback loop
(Buhler et. al, 2002).
The new participatory approach was first introduced in the late 1970s and the early 1980s. It has experienced changes and modifications as time has passed.
Limitations of participatory research have been encountered and are still debated in the
28 current extension literature. However, improvements to the approach have also been
made through attention to an increasing number of variables. For example, interactions
between farm and nonfarm activities, management of risk and uncertainty, environmental
degradation, and social equity are currently being addressed (Norman and Matlon, 2000).
Economic, social, and environmental dimensions are now part of the model, with the
ultimate goal not simply technology transfer and an increase in production, but an overall
sustainable livelihood for the producer (Norman and Matlon, 2000).
Conclusions
The relevance of the foregoing discussion for researchers is that a traditional,
quantitative social science approach to adoption of environmental technologies with the
diffusion of innovations model will not reveal all of the facets and intricacies of adoption,
due simply to the nature of the model. Attempts to discover the "independent variables"
that "explain" adoption are seen as ineffective because the geographic, socioeconomic,
and communication contexts matter a great deal in any given innovation-adoption
scenano. The quest to uncover a universal set of predictor variables appears to be the wrong approach to the diffusion puzzle (Brown, 1981 ). A multivariate regression analysis, for example, will typically have a low R-squared and thus leave more unexplained than explained.
A more effective approach may be to supplement the traditional approach with a more in-depth, qualitative examination of certain factors that may have more bearing on adoption of environmental technologies in a context of imperfect information channels in
29 a developing country. For example, in keeping with the earlier discussion of farmers' perceptions, one understudied factor among adoption studies is the question of farmers' concern for the environment. Another example is the more in-depth examination of the specific role that an environmentally-oriented extension agency such as the extension component at EAR TH University plays. In addition, the context of the adoption environment needs to be taken into consideration. These structural variables need to be considered, rather than just focusing on the individual-level characteristics of producers.
The classical innovation diffusion model, while highly criticized for many of the assumptions that it makes, continues to be highly valuable in terms of communication aspects. Keeping in mind the limitations that it presents, this study will utilize the model as part of the broader approach that was discussed above.
30 CHAPTER3
EARTH UNIVERSITY PROGRAM OF ECOTECHNOLOGY DISSEMINATION
In this chapter, the Parismina watershed, which is the region where EAR TH
University carries out its extension activities, will be described. Profiles of producers in
the watershed will be presented, along with general description of EAR TH University.
The components of EARTH's extension program are also discussed as are the principal
ecotechnologies disseminated by EAR TH.
The Parismina Watershed
The Parismina watershed is located in the humid tropics of Costa Rica in the
province of Limon. The study site was defined using this natural boundary, because
EAR TH extension efforts are limited to it. The watershed includes the counties of
Guacimo and Siquirres, and the larger settlements of Pocora and Guacimo.
The watershed can be divided into three sections: lower, upper and middle watershed areas. Altitude in the upper watershed varies from 200 to 400 meters, in the middle watershed from 75 to 200 meters, and in the lower watershed from 15 to 75 meters. The middle and lower watershed are characterized by more fertile soils, and contain most of the commercial agriculture. The upper elevations have marginal, rocky
31 soils, with much of the land in pasture or forest. Land use and agricultural activities vary
slightly based on elevation and soil types. Main agricultural activities of the small
producers include the production of staple crops such as cassava and other root crops,
maize, plantains, and beans. Other crops such as heart of palm, papaya and coffee are
produced for both self-consumption and market sales. Animal agriculture in the area
consists of chicken, pork, and beef production. Tilapia production is also becoming
popular.
The watershed is part of the Atlantic plain, and host to several multi-national
companies producing bananas and pineapple on large plantations. Costa Rica is the
world's second largest banana producer (FAO, 2004). Much of the banana production takes place on the Atlantic plain. Pineapple production has recently expanded in the area. It has surpassed coffee to become Costa Rica's second largest agricultural export behind bananas (FAO, 2004). The presence of both banana and pineapple production has made plantation work a major source of employment in the area.
The region was the site of colonization efforts beginning in the 1960s. They were both government-sponsored and spontaneous, and continued through the 1980s.
Historically, the province had been geographically isolated from the Central Valley where San Jose, the capital is located. The Cordillera Central served as this barrier.
Land passage to the province was only possible by a circuitous land route through
Turrialba or by air. Access to the region increased in the mid-l 980s when a highway was constructed through the mountain range connecting the capital with the Atlantic coast.
32 This important artery crosses the watershed and most of the larger town settlements are
situated along it.
The main highway is in fairly good condition, but the roads that network the rest
of the watershed are in relatively poor condition. There are two paved highways that
extend off the main highway that lead to larger communities in the upper and lower
watershed. However, the majority of the roads in the watershed are gravel. While cars
and trucks are able to pass over them, they generally inhibit travel.
The communities in the watershed are linked to other communities and cities
through a bus network. The bus system in Costa Rica is relatively reliable and is widely
used. Many public busses pass through smaller communities, although residents in rural
areas often have to walk quite a distance to catch the bus.
Because of the recent colonization and the even more recent road construction,
the watershed is host to fairly young communities inhabited by many residents coming
from other provinces in Costa Rica (Merida, 1997). These newly formed communities have electricity and most have access to potable water and telephone service. They are home to various community institutions such as churches (often Catholic and
Evangelical), primary schools, and community buildings. Typical community organizations include a women's group, farmers' association, sport committee, health committee, and educational committee (Merida, 1997).
33 Producer Profiles
In congruency with the "broadened view" of the classic model and adoption of
conservation technology this study aims for, qualitative data was also collected by the
researcher during the survey interview process and formulated into producer profiles.
Quantitative data is very useful in providing an overall picture of the situation in the
watershed, but little insight is gained on individual farmers, the composition of their
farms, and the issues that they currently face. It is very valuable to study the cases of
individual producers in order to better understand the composition of the various types of
producers that are found in the watershed. The following profiles were selected from
residents from various parts of the watershed in order to represent common types of
producers found in the area.
Producer 1
Producer 1 is a 76 year-old farmer who has been living in this area for the past 27
years. Originally from San Vicente Moravia (in the province of San Jose), he came to visit this area 27 years ago, and decided to stay. His main reason for leaving Moravia was that it was becoming urbanized, and he felt that the surrounding area was becoming environmentally contaminated as a result of this. He also remarked that many new people had moved to the area, and that it felt more like a city than the town he once knew.
He says that he is a farmer because it is a family tradition, because he likes the work and that is what he is used to doing. He also notes that he loves living in the
34 countryside, and commented that "there is nothing better than cultivating your own land."
Because of his advanced age, he has an employee who helps him with the farm duties.
Currently, Producer 1 owns 12.75 hectares of land in the Argentina area that he
bought when he moved to the community. He cultivates 1 hectare of palmito, and also
has about half a hectare of pasture. He has various fruit trees, and most of the fruit is
consumed by the family or given away to neighbors. Three beef cows, three horses, five
goats and 120 chickens can also be found on the farm. (While he does have three horses,
he said that his main form of transportation is walking and that he rarely leaves the
community.)
One interesting comment that he made was that when he first moved to Argentina,
no one locked their doors and people worried more about dogs and chickens wandering
into the house than thieves. He notes that when the highway opened up in the late 1980s,
the community rapidly changed and people had to start being more careful.
Producer 1 represents the category of producers which came to the area from
another province before the highway was opened. The characteristics of his farm are
very typical for the area, a medium-sized plot of land with a fairly diverse array of
animals and crops. Also very typical of the area, he has several hectares that he leaves forested and relatively untouched based on the value he places on nature.
Producers 2 and 3
Producers 2 and 3 are a married couple who share equally in the farm work and make important farming decisions together. The wife says that she is in charge of
35 planting and caring for the animals, while the husband is in charge of selling what they
produce. The husband told us: "I care for my land with my heart."
Their farm currently occupies one hectare of land that they bought ten years ago.
However, they do not have the actual title to the land, and are in the process of working
with a lawyer to try to obtain it. They explained that the land that they are currently on
was an abandoned plantation, and that they bought the land from a third party, and now
are being accused of being squatters (as are all their neighbors). Until the legal battle is
over, they have decided to hold off on making improvements on their farm, for fear that
they will be evicted.
However, they are interested in organic production and implementing eco
technologies. They have a biodigestor, which was installed three months ago and is fed
with the manure of their nine pigs. The wife noted that between the gas and fertilizer
production, the biodigestor "has really helped us economize."
The farm borders EARTH. The wife's brother currently works on the banana
plantation in EARTH, but neither husband nor wife has been on the EAR TH campus.
They view their contact with EARTH as being very positive, and are excited to learn more about eco-technologies that they can implement on their farm.
Currently they are cultivating malanga, yucca, plantain, banana, forraje and oranges. They have three milk cows, and besides selling milk they also make cheese and sour cream. They have nine pigs, two goats, thirty chickens, fourteen turkeys, three geese, and five ducks. (The survey questions had to be shouted over the din of all the squawking poultry.)
36 Producers 2 and 3 represent a category of producers who occupy a small plot of
land that they do not own the title for. Like many people in the area, they are interested
in implementing organic production and many of the technologies that EARTH promotes,
and have a very favorable opinion of the university and the work that they do. Also,
Producers 2 and 3 are representative of many couples surveyed that stated that they make
farming decisions together.
Producer 4
Farmer 4 currently owns 80 hectares in the middle watershed where EARTH
presently does not have much influence.
He is quite pessimistic about farming in his community, noting that production
costs are much higher than market prices. In fact, he has turned away from farming -
saying that it isn't worth the effort to plant anything anymore. If it isn't the prices,
people will steal right out of your fields, he says. He even used to have a fish pond where
he attempted to raise fish for sale and family consumption, but it was some distance from
the house which allowed people to easily steal the fish. After some time he abandoned
the idea.
When asked if individuals can make a difference in the environment, he continues on his pessimistic train of thought and told us "Here, we are invisible."
While this farmer still owns his land and has some crops planted currently
(papaya and ornamental plants), he has invested in a tractor and contracts out. In his opinion, this is a more reliable and profitable source of income.
37 Producer 4 is representative of some of the more pessimistic attitudes that are
prevalent in the watershed. While he has produced many of the newer and trendier
commodities such as tilapia and ornamental plants, he still finds it very hard to make a
living from farming. While continuing to reside on his farm and engaging in crop
production activities, he is representative of many of the producers who turn to other
sources of employment in order to sustain their livelihood.
Producer 5
Producer 5 is situated in the middle watershed, and his farm is located across the
road from a large pineapple plantation. He produces a variety of fruit, vegetables and
even organic rice. He sells his products at the farmers' market in Cariari.
In the past he had concentrated his farming efforts on cattle, but he had to sell
them shortly after the pineapple plantation was created in his community. The plantation
has brought a biting fly problem to the community, which is completely out of control.
He said that he couldn't stand to see his cows so miserable, so he sold them and
concentrated on crop production. Apparently, he has spoken with the pineapple plantations about compensation for his loss.
He is excited about new ideas and has tried a variety of new technologies and production practices. He learns about new ideas through contact with other innovative farmers and through the University of Heredia, EAR TH and a variety of other organizations.
He says he "is a friend of low-cost production", and is excited about
"recuperating" his soils. One of the ideas he has implemented through University of
38 Heredia is to encourage ant colonies in his papaya stands - the ants eat the larvae of
insects that frequently damage papaya. The ants serve as a natural form of insecticide.
Another practice he uses is through planting macuna, which is a fast-growing legume.
The legume first chokes out all the weeds in the area in which it grows, and then he can
harvest it, compost it and use it as a nitrogen source on his other crops.
Overall, Producer 5 is very excited about farming. He says "I feel really proud to
be a farmer - I've been one my whole life. I'm a farmer because it is the first thing I saw
how to do. I tried to work other jobs, but I couldn't do it - I didn't feel good about it."
However, he acknowledges what a struggle agriculture is: "Agriculture in this country is
not a secret from anyone - it is really hard to make it."
Producer 5 is representative of a class of producers who are very innovative and
have tried many new technologies, getting information from a variety of sources. This
class of producers tends to be highly concerned about environmental impacts. Also,
Producer 5, like many people in the watershed, has clearly experienced the impacts of the
expansion of pineapple production in the area. Many producers have been forced to
abandon cattle production due to the biting fly problem that the pineapple plantations have brought to the area. It is interesting that Producer 5 is extremely concerned about his own environmental impact, when there are such devastating environmental problems taking place in the area due to the pineapple plantations.
39 Producer 6
Producer 6 owned a total of eleven hectares that had been obtained through one of
the government organizations, Instituto de Desarollo Agrario (IDA). The family had
been on the land for 56 years.
Currently, EAR TH does not have much contact with producers in their
community. Producer 6 had not heard of many of the technologies mentioned in the
survey, but had heard of several of them through educational programming on television.
This producer noted that they gained most of their knowledge about EARTH through
conversations with other people.
Pineapple plantations are found nearby. Recently, representatives from the
pineapple companies have come to the house asking ifhe will sell the farm.
The family currently produces yucca, plantain and maize, but current prices for
these commodities are so low that they can't sell anything. Currently they have no farm
income, even though they have crops available for sale. Right now they are consuming
their crops and also giving them away to neighbors so they don't "rot in the fields". In order to sustain the family livelihood, Producer 6 had to go to work on a nearby pineapple plantation. A government pension that goes to the grandfather of the household also helps to sustain the family.
It should be noted that Producer 6 listed "walking" as his mam form of transportation. Without a means of transportation to get crops to market, producers such as these fall victim to intermediaries to buy their products and transport them to market.
40 It may be due to the transportation problem that Producer 6 finds it particularly difficult
to sell his crops.
Producer 6 is representative of a class of producers that have turned to nearby
plantations as a source of income due to the fact that the income generated by the farm is
not sufficient. Working off-farm may also limit the time that producers have available to
dedicate to farm changes and improvements, which may be reflected in rates of adoption
of agricultural practices. In addition, the problem of transporting products to market is a
common characteristic of many small producers in the area. Producer 6 is also
representative of a class of producers who have obtained their land through IDA.
EARTH University
EARTH University, located near Guacimo, Costa Rica, has an international
reputation for a strong commitment to the sustainable management of resources in the
humid tropics. It is a private non-profit institution that was founded in 1990. EARTH's
academic program focuses on agricultural sciences and natural resource management,
offering undergraduate degrees in agricultural engineering. Truly an international
university, faculty and students are drawn from all parts of the world.
EARTH University occupies a 3,000 hectare property that contains the university campus, teaching farms, agro-commercial businesses, extensive areas of production
(banana and pineapple), a 1,000 hectare biological reserve, a small hotel for visitors, and residences for professors and students.
41 EAR TH has had a profound impact on the surrounding community since its
founding seventeen years ago. As a world renowned institution, it has drawn many
professionals and their families to the community, and has given the opportunity for a
high quality education to many Costa Rican students. In addition, the university itself
provides many jobs for residents that live in nearby communities, and also provides direct
support to local producers by purchasing their products (e.g. milk, coffee and produce).
EARTH also implements a dynamic outreach program, which focuses the communities in
their watershed.
Perhaps one of the largest impacts that the university has made is through the
national and international visitors that are attracted to the university. Many of these
visitors come to learn about EARTH's work on sustainable agriculture and natural
resource conservation projects, while others come to conduct research or teach. Visitors
usually stay on campus, but they often eat at local restaurants and patronize local
businesses. In addition, many visitors visit local farms as agro-ecotourists.
While there are many positives surrounding the presence of EARTH m the
community, some residents have developed some negative reactions certain aspects of
EARTH's presence. For example, there is one main entrance to the campus that is situated on the main highway. This entrance has a gate that is guarded 24 hours a day and unless a person has specific business in the university or have arranged a tour, they are usually not allowed inside. In addition, all visitors that are allowed to enter must register at the gate with their passport or identity card. This system has caused some
42 people in the community to feel that the university is very isolated and closed off from
the community.
Since its founding, residents have had both positive and negative contact with
EARTH. Various rumors pass through the community, and some hint there is unequal
treatment of farmers. Some producers indicate that they would like students to come to
their farms (as described in the next section), but note that there are simply not enough
students to go around. In addition, some producers have participated in research projects
that they feel were abandoned or failed, leaving them with a bad impression of the
university.
Most of these negative opinions are inevitable, but are important to acknowledge.
It is likely that a large institution such as EAR TH that has a wealth of contact with the
local community will not be uniformly popular with the entire local population.
EARTH Extension
Data were collected through survey interviews in eight communities in the area
surrounding EARTH University. The eight communities were chosen to correspond to
one of two categories: four were identified as having a significant amount of direct
EARTH induced contact (within the past 5 years), while the other four have not had recent EARTH contact. A community that was categorized as having direct EARTH contact experienced EARTH agricultural extension programs implemented in the community through their Area de Desarrollo Agropecuario (ADE) division. This agricultural development program 1s a branch of the overarching extension program
43 Programa de Educacion Permanente (PEP), which also has programs that address
community development and small business formation.
The ADE mission is to increase the quality of life of EARTH neighbors in the
watershed, by promoting sustainable agricultural practices, participant research projects,
and the formation of production strategies that link producers with commercial markets.
For example, two specialized programs link the production and commercialization of
milk and coffee. EAR TH sponsors the initiative to increase the quality of the product and
connect producers with markets. Another featured program is the "Open Classroom"
which educates producers about sustainable agricultural practices that optimize their
production systems. EAR TH faculty members, assisted them with farm planning and
organization and also provide them with knowledge and tools to increase production on
their farms in environmentally sustainable ways (EARTH, 2005). Another component
of the agricultural development extension program is the "Work Experience Module".
This module matches third-year EARTH students with a producer in the community. It
assumes that information will be exchanged between them. EAR TH students are sensitized to the needs and experiences of producers in the community and are given the opportunity to share their knowledge of technologies and management principles that learned in the classroom. Students frequently help farmers implement new projects on their farms, providing the extra manpower and knowledge needed to get the projects started. Recently, students participating in the work experience module spend half of the module working with a producer as described, and the other half of the module working
44 in a local school. In the school, EAR TH students provide environmental awareness
education through a variety of activities and fieldtrips.
The Technologies
EARTH faculty and students are seriously involved in the discovery and
development of innovative new and sustainable agricultural practices and technologies.
They also work on the improvement and modification of already known technologies,
particularly those from other countries that can be adapted to the humid tropics. In doing
so, they consider the availability of local materials as well as the specific needs of the
local people. These technologies are passed on to local producers through the extension
processes outlined above. The producers often modify and improve the technologies
used on their farm through participant research that results from a continuing dialog with
EARTH.
Ten technologies and one management practice are currently being promoted in
the community through EAR TH extension programs. They represent components of an
integrated production system, but can also be used singly by farmers. Pedraza and Chara
(1997) explain an integrated production system (as cited in Cabezas and Botero 2001, pp.
2) as a system in which "each component takes advantage of the other, using everything that is produced as an input." Products that may typically be defined as waste become inputs for another part of the system in order to form a complete cycle that reduces the negative impact on the environment and is more sustainable. The Food and Agriculture
Organization of the United Nations defines the integration process as both" ... horizontal,
45 seeking improved management across components of the farming systems (including
resources, crops, livestock, forestry and fishery) and vertical, seeking improved
management of commodities through the production, processing, distribution and
marketing stages" (F AOa). The holistic approach of integrated production systems is
consistent with the sustainable agriculture goals of EARTH and with the mission of
improving the lives of producers in the watershed.
A previous study of the watershed (Dragon, 2005) focused on 31 producers who
participated in the work experience module in order to gain a better understanding of
their adoption, non-adoption and discontinued use of the various components of the
integrated production system that EARTH promotes. The current study focused on the
same technologies as the Dragon (2005) study in order to allow rates of adoption of those
who participated in the work experience module to be compared with the larger
watershed population. Findings from this study are compared with those from the other
study when appropriate (Dragon, 2005).
A description of each of the technologies follows. They are generally easy to use, maintain, and to modify to producer needs.
Animals and Crops
Generally speaking, animal and crop production are both important elements of an integrated production system because they lay the foundation for the rest of the system.
Both are important because they provide nourishment and/or income to producers, and the waste products become inputs to other parts of the system. Animal agriculture is a source of manure, which is then transformed into useful products through other elements
46 of the integrated production system. Crop production is also important because it
provides forage for animals, and the residuals can be used as inputs into the other parts of
the system.
Biodigestor
A biodigestor is a technology that allows the use of farm by-products, such as
animal manure, to be converted into methane gas and organic fertilizer (Botero, 2004).
EARTH disseminates information about small-scale biodigestors that are relatively
inexpensive and easy to install.
Animal manure is mixed with water and fermented in a large plastic bag that is
partially submerged in the ground. The water-manure mixture enters at one end,
ferments in the plastic bag, the methane gas collected, and eventually exits at the other
end. This affluent can be used as organic fertilizer, while the methane gas collected can
be used for cooking.
Residual waters from the biodigestor can also be further cleansed by passing
through various stages of a water decontamination system. The affluent waste water
can be pooled in channels and used for the production of aquatic plants. Aquatic plants
are characterized by high production of biomass, efficiency in cleaning polluted water
and adaptation to stress conditions. The water that has passed through channels with aquatic plants can then be used for the production of fish, such as tilapia (Cabezas and
Botero, 2001). The production of fish is another way to continue to decontaminate the affluent, and can also serve as a source of additional income and food.
47 Producers in the watershed have made modifications to these systems to fit their
needs. Some have made changes to the physical structure of the biodigestor, or have
tried various other inputs such as whey from cheese making and used cooking oil.
The biodigestor is an important aspect of the integrated production system
because it takes apparent waste products, such as animal manure, and converts them into
useful products which can be fed back into the system. The biodigestor helps to resolve
problems like management of human and animal excrements that pollute the ecosystem,
and creates a fuel that can be burned in place of firewood or purchased propane. In
addition, the production of aquatic plants can be a useful source of high protein animal
feed, and fish can serve as a source of additional income and food. Environmental
impacts are greatly mitigated after biodigestor affluent has passed through the various
stages of the system.
Nutritional Blocks
Nutritional blocks are a low-cost non-protein nitrogen supplement for ruminant
animals. They are composed of a diverse array of ingredients that are either mixed by the
farmer or can be bought pre-mixed. The main benefit of nutritional blocks is to increment the flora of the rumen to allow the animal to more efficiently utilize the nutrients that they consume (Botero, 2001 ).
Traditional Compost
According to the United States Composting Council (2002) compost is the product resulting from the controlled biological decomposition of organic material that has been stabilized to the point that it is beneficial to plant growth. It has the ability to
48 improve the chemical, physical, and biological characteristics of soils or growing media.
While it does contain plant nutrients, it is typically not characterized as a fertilizer.
Worm Compost
Worm composting is the process through which waste materials are transformed
into a material rich in nutrients that are readily available to plants with the aid of
earthworms. The addition of earthworms speeds the composting process. Like
traditional compost, worm compost can be added to agricultural land to improve soil
structure and fertility. It allows an immediate supply of plant nutrients, it also builds
reserves for future crops (Aranda, 1999).
Effective Microorganisms (EM)
Developed in Japan, EM is a mixture of naturally occurring microorganisms that
provide natural benefits. The mixture of microorganisms is formulated such that the
individual effect of each microorganism is magnified, and when applied to a system, it
reestablishes microbiological equilibrium.
EM provides a wide variety of benefits and can be applied in many different
ways. When applied to crops, it can increase production and help protect the crops from
insects and disease and it also improves soil conditions. When applied to animal production systems, it can be used to reduce odors and insects, decrease the amount of water needed to wash areas that the animals inhabit, and decrease animal stress and sickness. It also has beneficial qualities when fed to the animals as a supplement
(Fundaci6n de Asesorias, 2006).
49 Bokashi with EM
Bokashi is a fermented organic fertilizer made with animal manure that has a
variety of advantageous qualities. The use of bokashi with EM in areas where animals
are present keeps the odor down, limits the presence of insects, eliminates the need to
wash the stable floor which contaminates water, reduces labor, and decreases the
incidence of both mastitis and lameness in the animal population. When the bokashi is
finished fermenting it can be sold as organic fertilizer (Botero, 2002).
Forest Species
Trees are an important element of integrated production systems because they
offer many benefits such as the incorporation of organic matter in the soil, nitrogen
fixation, nutrient recycling, decreased erosion, and protection against the sun, rain and
wind. In addition, it helps to maintain a habitat for the flora and fauna native to the area.
For the farmer it represents a potential for the production of fruit, wood, charcoal, and
firewood (Cabezas and Botero, 2001; Botero and Russo 1997).
Agro-ecotourism
While the exact definition of ecotourism is problematic, it can be characterized as
"environmentally responsible travel to experience the natural areas and culture of a region while promoting conservation and economically contributing to local communities" (Furze, Lacy, and Birckhead, 1996: 149). Agro-ecotourism focuses specifically on the agriculture of a particular area, often through visits to local plantations, farms, and processing facilities.
50 Agro-ecotourism is a non-consumptive use of resources and has the potential to
serve both conservation and local development roles. "In terms of local development,
tourism can provide a vehicle or conduit for translating the values that others hold for a
natural area into benefits for those who live in or near it, and may therefore bear costs
associated with conserving the resource" (Furze, Lacy, and Birckhead, 1996: 146).
In the context of an integrated production system, agro-ecotourism provides direct
financial benefits that can be used for the maintenance of the system and the
implementation of other sustainable agriculture practices. While agro-ecotourism is not
in itself a technology, it is an important dimension of sustainable agriculture because it
communicates important information and values to visitors. In addition, it provides
producers with positive feedback for their sustainable agriculture and conservation
efforts.
La Argentina is a community near EAR TH University that has an association of
producers who offer agro-ecotourism services to national and international visitors.
Many of the farms feature different elements that go beyond sustainable agriculture practices or the integrated production system. These elements include hiking trails,
cabins, and offering typical food cooked with biogas (from a biodigestor).
Summary
The study focused on the Parismina watershed, located Costa Rica's province of
Limon. This watershed is characterized by several large plantations, with small producers occupying the more marginal land adjacent to them. Through a variety of
51 EARTH University activities, efforts are made to develop and diffuse environmentally friendly technologies to the small producer population in the watershed. The technologies chosen for this study are part of an integrated production system, which
EARTH is currently promoting. These technologies had been previously identified and studied in an earlier study of the watershed (Dragon, 2005).
52 CHAPTER4
METHODOLOGY
Basic methodological considerations that are related to statistical analyses found
in this thesis are presented in this chapter. It begins with a discussion of the data that
were used in the study, including the actual process of data collection and the sampling
procedure that was used to identify respondents for the field survey. This discussion is
followed by the presentation of a general model, including a series of empirical
hypotheses, which was used to guide the statistical analyses, a discussion of how the
variables in the model were measured, and the statistical method used to test the
hypotheses.
Sampling Procedure
Households were selected for interviews using a modified purposive sampling design. Upon entering a community, a farm household was selected at random, and every other farm household was surveyed after that until all houses had been approached or until dark.
A key informant was utilized during the survey process. This person also assisted with the distribution of the interviewers based on distance and density of farms. His
53 knowledge of the local area was very important to the process because many of the small
dirt roads in the watershed were not indicated on the map. The key informant input
ensured a more representative sample.
Data Collection
The Sample
In all, household data were collected through interviews with 185 individuals in
eight communities in the area surrounding EARTH University. These communities were
selected because they represent one of two categories: four have had a significant
amount of direct interaction with EARTH personnel within the past 5 years, while the
other four had not had EARTH contact over that period. "Influenced" communities
feature EARTH programs implemented through the Area de Desarrollo Agropecuario
(ADE), as explained in the previous chapter.
Interviews were conducted with self-identified heads of households on self
identified farms. If the head of household was not home, the location was not used and
the interview team moved on to the next appropriate residence. Interviews lasted on
average from 30 to 60 minutes. All of them were conducted in Spanish. They were conducted by EARTH students who were native Spanish speakers.
Pre-survey Preparation
Communities included in the survey were identified with the aid of EARTH faculty and PEP staff. The research team studied the layout of the watershed prior to the field survey. This involved visits by the principal investigator (PI) to all parts of the
54 watershed in the company of a local driver who also served as the key informant. As part
of this initial survey process, the key informant introduced the PI to many farmers in the
community and indicated the types of crops that were being produced at the different
locations in the watershed. The key informant also discussed the size, location and types
of plantations and farms in the region. He shared information about the types of
organizations that had been active in the region and discussed many of the problems
confronting producers in the watershed.
Survey Instrument
Respondents were asked to provide data on household demographic
characteristics, their attitudes towards environmental conservation, farm tenure and
agricultural practices, and prior interactions with EARTH University. One of the more
important segments of the interview consisted of a series of questions about nine different
environmental technologies currently promoted by EARTH. In addition to the nine
conservation practices specified in this section, respondents were also asked to name any
other conservation practices currently being used by them.
Attitudes about natural resource conservation and management were assessed
using questions from the Health of the Planet Survey (Dunlap, Gallup and Gallup, 1993).
They were translated into Spanish for use in this study. Selection was based on previous use. All had been previously used in both industrialized and developing countries.
Additional data on the diffusion-adoption process for eco-technologies in the watershed was collected by the interviewers. These data were essentially embellishments of responses to the specific survey questionnaires found in questionnaire used for the
55 study and were also provided by heads of households. These data were summarized at
the end of each day, and were used to develop farmer profiles.
The survey instrument was pre-tested several times and changes were made to
ensure that the questions were clear to respondents and reflected the type of information
that was being sought. Questions were reworded for clarity, and organized to allow for
better flow. Those deemed unnecessary were omitted to assure a reasonable survey
length.
Interviewers
The survey team consisted of EARTH students who expressed a desire for full
time work during their two-week vacation in August. All interviewers attended several
orientation sessions at which they became familiar with the survey instrument. They
were instructed on the basic principles of administering a survey and practiced interview
techniques. They were also taught the sampling procedure, how to identify the head of
household, and other germane topics.
General Model and Hypotheses
The model found in Figure 4.1 guided the data analysis. The model consists of a series of hypotheses of relationships between the adoption of conservation technologies and other variables found in the Rogers' model. The left side of the model represents relationships found in the classical adoption diffusion model. Independent variables related to the adoption of eco-technologies are socio-economic status, gender, level of concern about the environment, residence in a community impacted by EAR TH
56 Contact with EARTH Extension Program
-~---.,,,.,...,_,-- '------......
~--~o"oo_E_:~-:~~~-----·/)
/_,..-"' ____..._,..._ . ------....._.., ..---·------.. J ,.,.- EARTH Employment by ~\ Gender ·~~"~ Household Member _.,,.,,! (-""'- ___,,, I /(,_ .. -- 0-:=--::,~I I ~~-;.::.:;, u:::;~) ------~---- / .1 J.,__ Campus _,.,./... ,,------,, ...--- . ----'t_J--1 "'----~~------( SES )--t>( Technology Adoption ) ~--- __ _ Vl -....) '~~~--:,.//1''·------~\"\,/-----~~ttendanceat an EARTH~--,)
!/·-- · ---., \ "- Meeting or \\'orkshop ___,,, \ Fann Size "' "-.._.____ ------· -··~---_..__,,.,,___....--"'..,.,.,.,~... ------\ \ ------<"~THfatenst~~----\\ \(_. ..-- Residence in EARTH --.,,, 1 '"~-Cootact __,,,/ · Extension Influenced ) \\ Conununity ~- ",, ..______------__,..,..,, /./
\ ~..,.------.....-- ...... , \ / Priman· Source of -), ( Lt' • ·,_ .ullonnabon _,., ...... -.._ ..._____ , ______,,_,_------
Figure 4.1 The General Model programs, and farm size. The specific hypotheses found in this portion of the model are
listed below.
• Socioeconomic status is positively related to adoption of conservation
technologies and practices.
• Level of concern about the environment is positively related to the adoption of
conservation technologies.
• Living in a community affected by EARTH's extension program is positively
related to the adoption of conservation technologies and practices.
• Farm size is positively related to adoption of conservation technologies.
• Gender and age are positively significantly related to adoption of conservation
technologies.
The right side of the model represents the hypothesized influence of EAR TH
University outreach programs in the adoption of conservation technology behavior. Non
parametric statistics will be used asses the impact of different aspects of EAR TH
University's influence on the adoption of conservation technologies in the selected
communities. The specific hypotheses that will be tested using the non-parametric statistics are:
• Type of contact that respondents have with EARTH University is related to
technology adoption.
• The EARTH University extension endeavors vary according to conservation
technology.
58 • Overall, EARTH University is an important disseminator of information of
conservation technologies in the watershed.
Measurement of Variables
Most variables found in the model were measured using standard indicators. The
indicators have been used by other researchers in the conduct of previous field research.
Prior adoption research has shown that gender, socio-economic status (SES), age, and
farm size are important control variables
Gender
Gender was measured using a dummy variable with male being coded as 0 and
female as 1.
Farm size
Different forms of land use are evident in the watershed including renting, the use
of family land, and partnerships. They complicate the measurement of farm size. For
the purpose of this study, farm size was measured by the number of hectares under
cultivation by the household.
Concern about the environment
Concern about the environment was measured using an index consisting of the summer of responses to three questionnaire items. The questionnaire contained four related questions which are found in the Table 4.1. As shown in the table, three of the items tend to cluster while a fourth - rating of quality of community environment - largely fails to cluster with the others.
59 Environmental Concern Questions 1 2 3 4 Index 1. How concerned are you peronsally about environmental problems?
2. Overall, howm>uld you rate the quality of the environment in your community? 0.205* 3. How much, if at all, do you believe environmental problems affect your health? 0.325* 0.202* 4. How much, if at all, do you believe environmental problems will affect the health of our children and grandchildren in the next 25 years? 0.347* 0.072 0.415*
Index 0.718* 0.223* 0.783* 0.718* *Correlation is significant at the O.Ol level in a 2-tailed test
Table 4.1 Inter-item Correlation Matrix of Environmental Concern
Each question offered four alternative responses which varied from 1 - lowest level of concern for the environment to 4 - highest level of concern for the environment.
Individual index scores represent the sum of the scores from each item, thus ranging from
3 (lowest concern) to 12 (highest concern).
60 Socioeconomic Status Index
The socioeconomic status index consists of the sum of scores for monthly income and education level achieved. Raw scores for both variables were collapsed into low
(coded as 1), medium (coded as 2), and high categories (coded as 3). The frequency distributions for years of formal education are found in Table 4.2, as are the collapsed scores used for the index.
Score Education Frequency Score Freguenc:t 0 18 18 1 83 2 50 2 148 3 15 4 15 3 19 5 4
Table 4.2 Education Frequencies and Index Scores
Income is measured in co/ones generated by the household and included revenues generated from work outside of the residence as well as sale of crops.
61 Income Frequency Score
6,250 - 40,000 27 1
45 ,000 - 240,000 127 2
250,000 - 3,000,000 31 3
Table 4.3 Income Frequencies and Index Scores
Table 4.3 displays the frequencies and index scores for the income variable which were collapsed into three categories. As suggested by data in the table, the distribution approximates a normal distribution. As was the case for the environmental concern index, scores for education and income are summed across individual households yielding an index that ranged from a low of 2 to a high of six.
Education Income SES Index Education
Income 0.216*
SES Index 0.721 * 0.832* *Correlation is significant at the 0.01 level (2-tailed)
Table 4.4 Inter-item Correlation Matrix of Socioeconmic Status
62 Table 4.4 contains the inter-item correlation matrix of the variables in the socio
economic status index. The variables are correlated with each other at the .01 level.
Conservation Technology Adoption Index
The conservation technology adoption index was constructed using responses to
questions about the use of different technologies that households could have been using
at the time of the interview. The specific technologies included in the questionnaire are
listed below.
Conservation technologies referenced in questionnaire:
• Biodigestor • Nutritional Blocks • Traditional Compost • Worm Compost • Bokashi with EM • Fish Ponds • Decontamination ponds • Agro-ecotourism • EM • Forest Species • Medicinal Plants
"Forest species" and "medicinal plants" were deleted from the index because they were no believed to represent well "conservation" technologies. Responses to these
63 questions were coded 1 if being used by respondents and 0 if not being used by them.
Thus index scores range from 0 which indicates that the person is not currently using any
of the listed technologies, to 9 indicating that the person is using all nine technologies
listed.
EARTH University Influence
Household residence in a community impacted by EAR TH extension was coded
as 1 and non-residence in one of these communities was coded as 0.
Several other forms of influence are specified in the model. The first is whether
or not EAR TH is their primary source of information about each technology that they had
adopted. A dummy variable was created with EARTH as a primary source coded as l,
and other sources coded as 0. Hosting of an EARTH University student on their farm
through the Work Experience Module was another form of influence. This variables was
also coded 0 if the response was no and 1 if the response was yes.
A third form of influence was attendance at meetings or workshops sponsored by
EAR TH University. Consistent with the other items, it was coded as a dummy variable with 0 indicating no attendance and 1 indicating some attendance.
Visits to the EARTH University campus is another form of influence.
Respondents were asked if they had ever been on the grounds of EARTH campus.
Negative responses were scored 0 and positive responses were scored 1.
Employment at EARTH by a household member was yet another form of influence measured in the questionnaire. Lack of this employment was coded 0 and employment was coded 1.
64 Respondents who had adopted a technology were asked to indicate their primary
source of information about the technology. Sources of information other than EARTH
were scored 0 and EAR TH was scored as 1.
Statistical Test of Model and Hypotheses
The raw data from the survey was coded, entered into Microsoft Excel, and then
transferred to SPSS for statistical analysis. Data used to conduct the statistical test of the
model and hypotheses are found in the following section. Initially descriptive statistics
were used to describe the sample population, land tenure characteristics, levels of contact
with EARTH University, levels of concern about the environment, and attitudes towards
natural resource conservation. Formal tests of the hypotheses were based on parametric
as well as non-parametric statistics presented below.
Correlation Analysis
Relationships of independent variables found in the classical model with adoption
of conservation technologies were initially assessed through correlations. Pearsonian
correlations indicate whether or not there are significant linear relationships between variables. Product-moment correlation coefficients are measures of the linear relationships between two variables and the coefficient is one of the most widely used measures of relationships (Fraenkel and Wallen, 1996). It is calculated by summing the products of the deviations of the scores from the mean. It is symbolized in the equation below by the letter r.
L2x:zy r= N 65 The size of the correlation coefficient indicates the strength of the relationship
between the two variables. A perfect correlation has an absolute value of 1, and no
relationship has a value of 0.
The sign of the correlation coefficient indicates the direction of the relationship.
A positive correlation coefficient means that as the value of one variable increases the
other variable increases, and a negative correlation coefficient means that the value of
one variable increases the other decreases.
Multiple Regression
Multiple regression is a statistical technique that measures the relative relationship
of two or more independent variables with a dependent variable (Fraenkel and Wallen,
1996). This technique lowers the error of prediction and accounts for a greater
proportion of the variance of the dependent variable than do simple correlation
coefficients (Kachigan, 1986). This statistic is widely used in the social and natural
sciences. The general multiple regression equation is as follows:
y'= a+ b1x1 + b2x2 + ... bkxk
where Y' is the predicted value of the dependent variable and the independent variables are x 1, x2 ... Xk. The constant (a) and the slope (b) are determined from the sample data. 2 The coefficient of determination is symbolized by r . It indicates the percentage of the variance in scores for the dependent variable scores that can be attributed to differences in the scores of the independent variables (Fraenkel and Wallen, 1996).
This study will use an Ordinary Least Squares (OLS) regression of technology adoption on variables found in the classical adoption model in order to asses the relative
66 importance of these variables in predicting adoption. Age, gender, socio-economic
status, farm size, environmental concern, and community type are regressed on the
technology adoption index.
Chi Square Analyses
Chi square analyses were used to explore further the influence of EARTH on
adoption of conservation technologies. Non parametric techniques are used in this
analysis since the use of parametric statistics should generally be avoided when using
categorical data (Siegel, 1957).
The chi square is typically used to measure relationships among variables
measured with nominal or ordinal data. The statistic is based on a comparison between
expected frequencies and the actual frequencies of occurrence (Fraenkel and Wallen,
1996). Thus, the chi square is useful for determining if obtained frequencies are
significantly different than expected frequencies (Fraenkel and Wallen, 1996). The
equation for the chi square statistic is as follows:
x:i = 2:: (Obse:ived frequency - Expectedfrequency)2 Expected frequency
Variables included in the equation must be mutually exclusive (Kachigan, 1986).
Degrees of freedom are equal to k- 1, or one less the number of values of the categorical variable (Kachigan, 1986).
In this study the number of technologies adopted in communities with and without
EAR TH influence was investigated in order to better illustrate the difference in technology adoption between community types. Residence in a community influenced
67 by EARTH University was coded I while non-residence was coded 0. Adoption rates for
each category were then tabulated and entered into a two by two table.
This was followed by an analysis of the rate of adoption of individual
conservation and its relationship with EARTH University. Positive and negative
responses were calculated and then grouped by residence or non-residence in EAR TH
University influenced community. Chi squares were then performed for each of the
technologies.
In order to further understand the specific source of information from EAR TH,
chi square analyses were then conducted of the relationships between adoption of specific
technologies and the principal forms of EARTH University influence, namely, hosting a
student, attending a meeting or workshop, employment at EARTH, and visiting EARTH
campus). These analyses provide greater insight into the levels and type of influence that
EARTH University has on conservation technology adoption in the watershed.
Summary
An overview of basic methodological tools used in the analyses found in this these are presented in the chapter, beginning with an overview of the data collegian process. This was provided to give the reader a greater understanding of the relative reliability of the data collected. The model used to guide the statistical analysis, including hypotheses that can be tested was also presented. The measurement of the variables found in the model and hypotheses was also described in order to allow the reader to assess relative reliability and validity of the measurement process. Finally,
68 statistical tests used in the following chapter to assess the validity of the model for conservation technology were described.
69 CHAPTERS
RESULTS AND DISCUSSION
This chapter contains data from the Parismina Watershed, which are used to
assess the validity of the model guiding this study along with the hypotheses
contained therein. Initially, descriptive statistics are presented in order to provide the
reader with a fuller understanding of who the respondents were. Data are also
presented which describe land tenure characteristics, the relationship of the
respondents to EARTH University, and their attitudes towards the environment. This
section is followed by a statistical test of the model beginning with a test of the
hypotheses contained therein, followed by a test of the relative importance of
variables as predictors of adoption, using a multiple regression model. This is
followed by an analysis of the relative importance of EARTH University contact on eco-technology adoption using chi-square analysis.
Frequency Distribution of Variables in the Model
Descriptive Statistics
A total of 185 producers were surveyed from communities in the Parismina
Watershed. Demographic characteristics of the respondent pool are displayed in
70 Table 5.1. Respondents range in age from 20 to 85 years, with the average age being
49 years. This distribution suggests that rural households in the watershed are lead by
middle age persons, with the majority ranging from 36 to 62 years of age (one
standard deviation from the mean).
Background Variables Minimum Maximum Mean Std. Deviation
Gender 0 1 0.24 0.43
Age 20 85 49.63 13.91
Siz.e ofhousehold 1 19 4.22 2.07
Household income 6250 3000000 196596.47 319550.44
Table 5.1 Descriptive Statistics of Respondents
The number of household members varies from one to 19, with the average being
four. This again suggests that households in the region have undergone the
demographic transition, with most families consisting of from 2 to 6 people. Average
household income is roughly 196,000 colones per month, or approximately
US$400/month. These households are representative of a rural middle economic class.
71 Level of Education Freguency Percent No fonnal education 18 9.7 Some primary 83 44.9 Primary completed 50 27.0 Some secondary 15 8.1 Secondary completed 15 8.1 University completed 4 2.2 Total 185 100.0
Table 5.2 Education of respondents
Table 5.2 displays the frequencies of the level of education of survey
respondents. Nearly ten percent had no formal education, but the majority of
respondents had at least some primary education. Twenty-seven percent of
respondents had completed their primary education, and sixteen percent had
continued on to complete a portion of or graduate from secondary school. Four of the
respondents had completed a university degree. These data also suggest that the
respondents represent a rural middle class. Children of the respondents have greater
access to education and are likely to take advantage of secondary education
opportunities to a greater extent that their parents for this very reason.
Land Tenure
Land tenure characteristics are displayed in Table 5.3. Size of properties controlled by households varies from less than one to 250 hectares. The amount of 72 Minimum Maximmn Mean Std. Deviation
Hectares Omied 0.25 250 12.12 23.98
Hectares Rented 1 110 12.92 29.30
Hectares Cultivatec 0 210 10.94 22.34
Title 0 1 0.75 0.43
Years in family 0.5 71 19.38 13.24
Government help 0 1 0.23 0.42
Table 5.3 Land Tenure Characteristics
land actually cultivated by individual producers ranged from less than one to 210
hectares, with the average being 10.9 hectares. Of the 185 producers surveyed,
thirteen or about seven percent indicated that they rent land. The amount of land
rented ranged from one to 110 hectares, with the average being about 13 hectares.
Seventy-five percent of producers indicated that they had title deed to the land that
they owned, and 23 percent had obtained the title through the aid of a government program. Respondents were also asked how long their land had been in the family.
Answers varied from one to 71 years, with a mean of 19 years. This mean number suggests that most land owners moved into the region about the time that the road from San Jose to Limon was completed.
73 Contact with EARTH University
The extent to which respondents have had contact with EAR TH University
and the way they have interacted with it are found in Table 5.4. All but ten of the
respondents had heard of EARTH University. Forty-three percent of them had
Yes No !2!!! Type of Contact with EAR1H Freguency Percent Freguency Percent Freguency Percent Heard of EARIB 175 95 10 5 185 100 Hosted a student 63 35 122 65 185 100 Attended a meeting or activity 77 43 108 57 185 100 Visited campus 126 71 59 29 185 100 EARIB employment 46 28 139 72 185 100 Current EARm employment 31 17 154 83 185 100
Table 5.4 EARm Contact Frequencies
attended a meeting or other activity hosted by EARTH, and 71 percent of them had
visited EARTH's campus at least once in the past. Over one-third ofrespondents had
hosted a student on their farm in the past three years through the work experience module. When asked if anyone in their household worked at EAR TH, 46 respondents indicated that a member of their household is currently working or had worked in the past at EARTH. And roughly two thirds of those are currently employed by EARTH.
Thus, it is evident that EARTH University has an important economic impact on the watershed through the employment which it provides as well as its impact on farming and the landscape.
74 Concern for the Environment
As described in the methodology chapter, a concern for the environment index
was constructed using three items that linked the environment to community well
being. Frequencies are displayed in Table 5.5.
Score Frequency Percent
5 1 1 6 1 1 7 3 2 8 8 4 9 6 3 10 13 7 11 25 14 12 35 19 13 49 26 14 30 16 15 12 6 16 2 1 Total 185 100
Table 5.5 Environmental Attitudes lnde x
Values range from 4 to 12, with 12 representing the greatest concern for the
environment. As evident in the table, respondents are generally very concerned about
environment as it relates to their communities of residence. The distribution is highly skewed to the right. Twelve percent of them had maximum scores and about two thirds of them had scores ranging from 10 to 12. This suggests that they are aware of
75 the potential negative environmental impacts of large plantations in the region as well
as the need to conserve the natural resource base of the region.
Adoption of Eco-technologies
The distribution of frequency of use of eco-technologies that are being
proposed by EARTH University is found in Table 5.6.
Number of Frequency Percent Technologies 0 102 55 1 43 23 2 21 11 3 8 4 4 6 3 5 1 1 6 3 2 7 1 1 Total 185 100
Table 5.6 Number of technologies currently in use
The responses range from zero to seven. Across the eight communities surveyed, a majority of the households were not using any of the conservation technologies. Only 23 percent of the households reported using one, and only 11 percent reported using two of them. Those using three or more only accounted for 11 percent of all of the households. These data are inconsistent with those presented
76 above on concern for the environment. The latter suggest a high level of concern, whereas the data on actual practice suggest the opposite.
Statistical Test of Model
Test of Hypotheses in Model
The hypotheses involved in the classical model were initially tested through the use of bivariate correlations which are presented in Table 5.7. Conservation technology adoption is significantly and positively correlated with residence in
EARTH contact communities (r = .11), SES (r = .13), environmental concern (r =.15).
77 X1 X2 X3 ~ Xs ~ X1
EARTH Contact Community- X1 -.14 .06 -.01 -.09 .05 .11 *
Concern for Environment - X2 -.19*** .07 .16** .07 .15**
Gender-X3 -.11 -.07 -.12 -.13**
Age-~ -.33** .02 -.06
Socio-Economic Status -X5 .26** .13**
Hectares Cultivated - X6 .21 ***
Technology Adoption-X1
Mean 0.53 9.75 0.24 49.63 4.03 10.94 0.88 Standard Deviation 0.50 1.70 0.43 13.91 0.79 22.34 1.35 * Correlation significant at p < .05 **Correlation significant at p < .01 *** Correlation significant at p < .001
Table 5.7: Correlation Matrix for Variables in Traditional Diffusion-Adoption Model
and hectares cultivated (r = .21 ). In addition, technology adoption is correlated to gender
(-0.128), with men being more likely to adopt conservation technologies. Age is not significantly correlated with technology adoption, and will be excluded from further analysis.
78 Relative Importance of Variables in the Model
Table 5.8 contains the results of the Ordinary Least Squares Regression of
number of technologies adopted on gender, SES, EARTH influence, concern for the
environment and hectares cultivated.
Independent Variables b s.e {3
Gender -0.270 0.230 -0.086
Socioeconomic status 0.114 0.128 0.067
Corrnmmity influenced by EARTH? 0.353* 0.195 0.131
Concern fur envirornnent 0.099* 0.059 0.126
Hectares under cultivation 0.010** 0.004 0.131
Constant -0.780 R2 0.063 S.E.E. 1.303 N=I85 *Significant at p<.05 for a I-tailed test **Significant at p<.OI for a I-tailed test
Table 5.8 OLS Regression of Technologies Adopted on Gender, SES, EARTH Influence, Concern For Environment, and Hectares Cultivated
For this model, the effects of gender and socioeconomic status did not have statistically significant effects on adoption. However, living in an EARTH University
79 contact community did have a statistically significant influence on adoption. The
interpretation of this statistic is that individuals living in communities in which EARTH
University actively promulgates eco-technologies adopted on average 0.353 more
environmental technologies than individuals in non-influenced communities. Concern
for the environment is also significantly related to the adoption of eco-technologies. For
each additional point on the environmental concern index, an individual adopted on
average 0.099 more environmental technologies. The variable with the greatest impact
on eco-technology adoption was the number of hectares cultivated plot. This suggests
that economic conditions also have an impact on adoption of eco-technologies, despite
the non-statistically significant regression coefficient for SES. On average, it appears
that concern for the environment and contact with EAR TH University extension
programs that related to environmental factors are the most important predictors of
adoption of eco-technologies.
Results from the regression model support three of the original hypotheses,
namely, that living in an EAR TH contact community is related to the adoption of
conservation technologies; concern for the environment is related to the adoption of conservation technologies; and farm size is related to the adoption of conservation technologies. Socioeconomic status and gender do not have statistically significant relationships to the adoption of eco-technologies. In these cases the null hypothesis of no relationship is retained.
The regression model thus proves helpful for understanding patterns of adoption of these technologies, but in another sense it underscores the whole critique outlined in
80 the literature review about the limited utility of such a traditional approach. Confirming
2 the warning from above, the R value indicates that the model accounts for only 6% of
the variation in adoption of environmental technologies, a low figure even by the more
tolerant standards of the social sciences. However, the descriptive statistics and results
from the chi square analysis found in the following section further reveal the impact that
EARTH has on adoption of these technologies.
Impact of EAR TH Contact on Adoption of Eco-technologies
Residence in EARTH Contact Community
Quantitative analysis of the data is continued with a more in-depth examination of
the specific influence that EARTH is having on the adoption of their most heavily
promoted environmental technologies within the surrounding communities. Table 5.9
indicates the number of households within EAR TH influenced and non-influenced
communities who have adopted different environmental technologies.
It shows the frequencies and percentages of adoption of each technology and the
differences in adoption between influenced and non-influenced communities. Overall,
there is a very low rate of adoption of all technologies, regardless of any influence
EARTH has on a community. Biodigestors have the highest rate of adoption of any of the nine named technologies, with 21 individuals or 11 percent of the sample indicating that they currently use a bio-digester. Two technologies, biodigestors and worm compost, are the only two which have a significantly higher rate of adoption in influenced communities than in non-influenced communities. There was no difference
81 between the numbers of technologies adopted in the two types of communities, which may be indicative of the influence of other extension organizations that operate in the area.
Community with direct EAR1H participation? Eco technology Yes No Total Frequenc)' Percent Frequency Percent Frequency Percent
Biodigestor* * 16 16° 5 6 21 llA Nutritional Blocks 7 7 7 8 14 8 Traditional Compost 10 10 11 13 21 11 Worm Compost** 9 9 2 2 11 6 Bokashi con EM 3 3 4 5 7 4 Fish Ponds 8 8 6 7 14 8 Discontamination w/ponds 2 2 2 2 4 2 .A.gro-ecotourisrn 6 6 5 6 11 6 EM 9 9 3 3 12 6 Other ecotechnology 26 27 15 17 41 22 .A.t least one adoption 45 46 38 44 83 45 More than one adoption* 26 27 14 16 40 22 Total innovations adopted 96 62 60 38 156 100 Total subjects interviewed 98 53 87 47 185 100 • Chi square test for difference, p<. l 0 •• Chi square test for difference, p<.05
0 Percentages represent the mnnber of people within a given commllllity type. For example, 16% of subjects in EARTH-infl commllllities adopted biodigestors. "Percentages represent the total nurrber of technologies. For exarJl)le, biodigestors represent 11% of all technologies
Table 5.9: Number of Ecotechnologies Adopted in Communities With and Without Direct Participation by EARTH University
82 EAR TH appears to have more influence on the dissemination of particular
technologies. This is probably due to the fact that these technologies are more heavily
promoted or promoted more effectively than the other technologies. It may be indicative
that other organizations promote some of the technologies but not all, leaving a niche for
EARTH to be the sole promoter of certain technologies. In addition, these technologies
may be viewed as more socially acceptable to producers in the watershed, or may be
characterized by a higher perceived profitability.
The rate of adoption of at least one environmental technology does not differ
significantly between the two community types. However, the level of adoption of at
least two across the two community types is significantly different at the p<. l 0 level,
with over a quarter of all individuals in EARTH-influenced communities adopting
multiple technologies, compared to only 16% in non-influenced communities. Adopting
multiple technologies is a sign of a more proactive environmental approach to farming,
and it is here that we see the influence of EAR TH participation in the communities.
Primary Source of Contact and Eco-technology Adoption
A second way to measure the influence of EARTH is to assess the primary source
of information that spurred them to adopt a given technology. Results are presented in
Table 5.10.
EARTH University outreach activity apparently has a differential impact on the adoption of certain technologies. For example, in the case of traditional organic compost adopters in EARTH-influenced communities were six times more likely to name EARTH as their primary source of information than those in non-influenced communities. A
83 significant influence also exists for pond decontamination systems and the development of agro-ecotourism activities. More importantly, when information sources for all adoptions are considered, the influence of EARTH is clear. Over half of all adopters in
EAR TH influenced communities named EAR TH as their primary information source, compared to less than one-fifth in non-influenced communities.
Residence in EARTH Influenced Community Yes No Total EARTH as Primary EARTH as Primary EARTH as Primary primary source other primary source other primary source other Ecoteclmology source than EARTH source than EARTH source than EARTH Biodigestor 11 5 2 3 13 8 69% 0 31% 40% 60% 62%" 38% Nutritional Blocks 2 5 1 6 3 11 29% 71% 14% 86% 21% 79% Traditional Compost* 6 4 1 10 7 14 60% 40% 9% 91% 33% 67% Worm Compost 5 4 0 2 5 6 56% 44% 0% 100% 45% 55% Bokashi con EM 2 2 2 4 3 67% 33% 50% 50% 57% 43% Fish Ponds 0 8 0 6 0 14 0% 100% 0% 100% 0% 100% Discontamination w/ponds* 2 0 0 2 2 2 100% 0% 0% 100% 50% 50% ~gro-ecotourisrn* 4 2 0 5 4 7 67% 33% 0% 100% 36% 64% EM 6 3 2 1 8 4 67% 33% 67% 33% 67% 33% Other ecoteclmology 13 13 3 12 16 25 50% 50% 20% 80% 39% 61'Yo All adoptions** 51 45 11 49 62 94 53% 47% 18% 82% 40% 60% • Chi square test of difference, p<.05 •• Chi square test of difference, p<.00 I
0 Percentages represent all adopters of the given technology in the given community type. For example, 69% of all biodigestor adopters living in EARTH-influenced communities listed EARTH as their primary source of information regarding biodigestors. "'Percentages represent the total nwnber of technologies adopted in which EARTH wa.s named as the primary source of information. For exarrple, 62% of those who adopted a biodigestor narred EARTH as the primary source of information.
Table 5.10: Primary source of information listed by ecotechnology adopters
84 EARTH Extension Activities and Environmental Technology Adoption
EARTH extension is multi-faceted and information flows from the university to producers through a variety of channels. The main outreach channels are highlighted in
Table 5.11 below, with the corresponding number of adopters and non-adopters that correspond with each category.
Participation in EARIB Activity? Adopters Non-Adopters Extension Activity Yes No Yes No
33 50 30 72 Hosted EARTH student 40% 60% 29% 71%
Member ofhousehold 27 56 20 82 employed by EARTH* 33% 67% 20% 80%
Visited EARTH 66 17 60 42 Campus** 80% 20% 59% 41%
Attended meeting or 49 34 28 74 workshop*** 59% 41% 27% 73% * Chi square test of difference, p<.05 **Chi square test of difference, p<.01 *** Chi square test of difference, p<.001
Table 5.11 EAR m Extension Activities and Adoption of One or More Environmental Technologies
85 Hosting an EARTH student was not differentially related to adoption.
Employment of a household member by EAR TH University is associated with eco
technology adoption at the .05 level. Visiting the EARTH campus was significant at the
.01 level. And attending a meeting or workshop organized by Earth University was
significantly associated with level of technology adoption at the .001 level. In short, the
specific types of EAR TH contact are shown to have different impacts on the adoption of
environmental technologies. As hypothesized, it was found that the different EARTH
extension activities vary in significance when compared to the adoption of technologies.
Surprisingly, hosting a student on the farm through the work experience module
was not a significant factor related to adoption. During the course of the module,
students in this program specifically promote these technologies to the producers that
they work with. A previous study of the diffusion of technologies through the work
experience module in the watershed (Dragon, 2005) indicated that producers view
students as "access points" but not necessarily as experts in the field (p.177). The study
also found that when a faculty member also interacted with farmers, they were more likely to test a new technology or practice than when they only interacted with students.
Dragon (2005) found that the producers viewed EAR TH students primarily as motivators.
Producers' tendencies to try new things dropped when the students stopped their interaction with them. In fact, many producers in the study discontinued the use of many technologies after the students left. The Dragon (2005) study illuminated some of the issues related to the adoption of technologies among participants in the work experience module, while the present study extends beyond those participants in order to understand
86 the relative importance of the module compared to other extension activities. Indeed, while the work experience module seems to be a positive experience for both producer and student, it is not the most effective strategy for the promotion and adoption of conservation technologies.
Employment of a household member at EARTH was related to adoption, but even more significant was visiting the EARTH University campus. Both employment by
EARTH University and visiting its campus offer the opportunity to see some of the technologies in use, as well as interact with the people who develop and maintain these technologies. Seeing a technology being used in field trials refers to the concept of
"trialability." Rogers (2003) argued that it is a very important aspect related to adoption.
The most significant extension activity related to adoption was attending a meeting or a workshop hosted by EARTH. EARTH offers an array of classes, workshops, and meetings revolving around various topics. Attendance at one of these events involves interaction with EARTH faculty, extension staff and perhaps students. In addition, farmers are exposed to their peers who may have adopted technologies. Attending EARTH sponsored events may be a significant factor affecting adoption because they not only bring various EARTH related personnel together with producers, but also bring the producers themselves together to foster the formation of interpersonal networks.
Summary
87 Data presented in this chapter suggest that the diffusion model propagated by
Rogers and his associated is useful in explaining the adoption of eco-technologies in the
Parismina watershed. All of the variables found in the diffusion model were correlated with adoption, less for age. However, the regression data indicate that attitudes towards the environment and the impact of EARTH University's outreach program have an important impact on the adoption of eco-technologies. The effect of socio-economic status on adoption behavior was not statistically significant in the model. On the other hand, economic factors remain important as evidenced by the important effects of size of farm operation.
The data also indicated that the EARTH outreach program has an important impact on the eco-technology adoption behavior of farm households in the Parismina watershed. These impacts vary depending on the type and intensity of interaction represented by them.
88 CHAPTER6
SUMMARY AND CONCLUSIONS
Summary
Considerable debate exists m the literature about the ability of the classical
diffusion model to explain the adoption of different types of innovations. The adoption
of environmental as opposed to commercial technologies is a phenomenon still not fully
understood in the sociological literature. In particular, patterns of adoption of
environmental technologies remain understudied in Latin American countries.
The purpose of this study was to assess the relative importance of variables found
in the classical diffusion model popularized by Rogers and his associates in explaining
the adoption of eco-technologies by farm households in Costa Rica. The study was
conducted in the Parismina watershed, which is located on the Atlantic coast tropical region. It focused on over a decade of outreach and engagement activity by EARTH
University, which is located in this watershed, with the local population. In addition to
89 interpreting the relative importance of factors found in the diffusion model, other factors
were also examined, such as the level of concern for the environment held by farmers and
the outreach activities of EAR TH University. In effect these two variables can be
conceptualized as variations in the operationalization of attitudes towards adoption and
contact with extension agents and their parent organizations. The latter was measured in
a number of ways, including contacts with students, faculty members and direct contact
with the EARTH University campus.
Data for this study are from a survey of farm households in the watershed. Data
were gathered in eight communities, which included four that were classified as "EARTH
University contact communities" meaning that they were targeted for outreach activity by
the university, and had had a significant amount of direct interaction with EARTH
personnel within the past 5 years. The other four communities did not have such
concentrated exposure to EAR TH extension programs.
A total of 185 household surveys were completed. Data were collected on
household demographic characteristics, attitudes towards environmental conservation,
farm tenure and agricultural practices, and prior interactions with EARTH University. In
addition, a series of questions about nine different environmental technologies currently
promoted by EAR TH were included.
Overall adoption rates of environmental technologies in the watershed were very
low. Many of the producers included in this survey are resource-poor farmers on marginal land. Although mindful of the need to conserve the natural resource base, their primary concern appeared to be short-term survival. Short-term concerns take
90 precedence in times of economic stress and long-term environmental conservation are of
lesser priority during these periods (Swanson et al, 1986). Currently, no government
programs subsidize any of these technologies. Farmers in the watershed adopt
technologies on a voluntary basis, which may help to explain the relatively low levels of
adoption.
Test of Model
Socioeconomic status as measured by income and level of education was
hypothesized to be directly related to adoption of conservation technologies and
practices. The correlation between these two variables was in fact significant. However,
the regression coefficient for adoption on socio-economic status within the model was not
statistically significant. This may be explained by the statistical significance of number
of hectares cultivated in explaining adoption within the model. The correlation between
number of hectares cultivated and socio-economic status was also significant, so the
former could be viewed as another indicator of socio-economic status.
Gender was also hypothesized to be related to the adoption of conservation
technologies. The zero order correlation was significant at the p :s_ .05 level suggesting
that households with male heads are more likely to adopt them. The regression of
adoption of eco-technologies on gender, however, was not statistically significant so its
use as a predictor of adoption of conservation practices is limited.
Attitudes towards the environment were also hypothesized to be related to adoption of conservation technologies. They were measured with an index consisting of items dealing with level of concern for the environment. This variable was also
91 significantly correlated with the adoption of conservation technologies. Furthermore, the
regression of adoption on the index as also statistically significant at the p .:S .05 level,
suggesting that it has an important independent effort on adoption.
The importance of contact with sources of knowledge about practices on the
adoption of them was also tested. In the classical model, this is typically represented by
contact with extension agents. In this case, it was measured by residence in a community
that was targeted by EARTH University to one for outreach and engagement. The
correlation between residence in an EAR TH contact community and level of adoption
was statistically significant at the p .:S .10 level. In the regression model the regression
coefficient was statistically significant at the p .:S .05 level suggesting that it also has an
important independent effect on the adoption of conservation technologies.
EARTH University was found to be important disseminator of information of
conservation technologies in the watershed. Adoption of multiple technologies is
significantly higher in communities identified as having more EARTH influence. In
addition, adopters of certain conservation technologies cited EAR TH as their main source
of information significantly more often than other sources of information.
In order to assess more adequately the impact that EARTH University outreach
and engagement efforts were having on resident populations in the watershed, further
detailed analyses were done of the relative impact of these activities on the adoption behavior of its residents. The general hypothesis that guided this analysis was that there are significant differences in technology adoption due to the nature of contact that respondents have with EARTH University. This study found that hosting a student
92 through the work experience module did not lead to significantly greater conservation
technology adoption. Apparently, farmers in the region consider the students to be
important in raising the level of awareness of these technologies, but not convincing in
their arguments for their adoption, at least when compare to faculty members at EAR TH
University. However, employment of a household member at EARTH, visiting EARTH
campus and attendance at an EARTH meeting or workshop were all significantly related
to conservation technology adoption. In fact, it appears that the more the direct contact
with EARTH related to specific conservation technologies, the more likely it is that
households will adopt them. Attendance at EAR TH meetings was most highly associated
with the adoption of conservation technologies.
In summary, the classical model, which focuses on individual characteristics as
important factors of adoption, was found to be of limited use for the adoption of
conservation technologies in the Parismina watershed. Socioeconomic status, age and
gender were not statistically significant in the model. On the other hand, attitudinal and
extension contact variables related specifically to conservation technologies were
important predictors of adoption of eco-technologies. The outreach and engagement
efforts of EAR TH University on its surrounding communities were shown to have had an
effect over the years. Those activities that directly engage the rural farmers in discussion
of the technologies appear to be most effective.
Concern for the environmental concern was found to be significantly related to
the adoption of conservation technologies in this study. Conflicting findings exist in the literature regarding the relationship between environmental concern and adoption.
93 Considering the nature of EAR TH extension and their focus on the environment, it is not surprising that this environmental concern is transferred to the producers in the surrounding communities. This relationship may have also been more significant in this study because of the relatively higher standard of living of farmers in the watershed, compared to farmers in many other tropical nations.
Study Limitations
Several methodological considerations deserve mention here. Although the eight communities were divided into those directly "influenced" and "not influenced" by
EARTH, in truth the borders between the two community types are porous. Community borders are not well defined, and to define areas of EARTH influence/non-influence is even more problematic. For example, residents from both influenced and non-influenced communities work at EAR TH. And this distinction fails to recognize that an important part of the diffusion process is word-of-mouth contact between farmers who are in all likelihood communicating with each other across all of the communities included in the study.
The measurement of environmental attitudes was also problematic. The attitudinal questions used in this study were taken from the Health of the Planet Survey
(Dunlap, Gallup and Gallup, 1993) and had been translated into different languages and used in surveys in a variety of industrialized and developing countries. However, the questions are subject to a different interpretation by respondents from different countries.
They are influenced by culture, values, and environment. The respondents in this survey often commented on the environment in their community, often rating it as "poor" but
94 then specifically asked the interviewer to mark their answer as "fair" or "good" because they didn't want to appear too pessimistic. This is typical of the Costa Rican culture.
Further Research
EAR TH University has been successful in disseminating sustainable agriculture practices to the population that surrounds its campus. However, it appears that it has achieved more success in promoting certain technologies rather than others. Future studies could investigate the reasons why this is so. Reasons may lie with perceived profitability and risk, or even the social acceptability of the technology. In addition, costs associated with the installation and maintenance of the technologies should be taken into account in future studies. Future research should identify and research other barriers to adoption, including structural factors which were not considered in this study.
Another topic for future adoption studies in a developing country context should be the dissemination of information via farmer-to-farmer networks rather than official extension agents. Differential rates of adoption in countries with information channels quite distinct from those we take for granted may be partially accounted for by the strength or weakness of these informal local ties.
In general, however, the index did prove to be useful and further studies should continue to focus on the importance of There might very well be stronger correlations between environmental attitudes and adoption, but because of this measurement problem the true correlation between these variables is unclear.
95 Attitude towards environmental conservation was shown to be an important factor in the adoption of eco-technologies, and thus, in the promulgation of agriculture that could be viewed as more sustainable in the long run. The index used in this study has been used in other cross-cultural settings. It is recommended that further analyses be done of its reliability and validity for Central America and other Latin American cultural settings. It may require further adaptation for future studies.
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102 APPENDIX
Survey of the Diffusion of Eco-Technologies in the Parismina Watershed
Ntimero de Identificaci6n:
0.2 Entrevistador:
0.3 Fecha:
0.4 Lugar (Comunidad):
0.5 Coordinadas de GPS:
0.6 Tipo de casa: 1 Madera, mala condicion 2 Madera, buena condicion 3 Concreto, mala condicion 4 Concreto, buena condicion 5 Concreto, excelente condicion, grande Pre-encuesta preguntas:
(,Considera Ud que esta es una finca? i,Usted cultiva su tierra o tiene animales? (,Producen algo?
(,Quien toma las decisiones importantes en la finca?
103 Secci6n 1 : Actitudes con respecto al Media Ambiente
1.1 lQue tan preocupado esta Ud. de los problemas ambientales - diria Ud., muy preocupado, preocupado, no muy preocupado, o no estoy preocupado? _ Muy preocupado (1) _ Preocupado (2) _No muypreocupado (3) _ No preocupado (4)
1.2 l,C6mo evaluaria Ud. la calidad del Medio Ambiente aqui en su comunidad? _ Muy buena (1) Bastanta buena (2) Bastanta mala (3) _Muymala (4)
1.3 l,Cuanto cree Ud. que los problemas ambientales afectan su salud? Gran canti dad ( 1) Bastante (2) No mucho (3) Paranada (4)
1.4 l,Cuanto cree Ud. que los problemas ambientales afectaran la salud de nuestros hijos y nietos en los pr6ximos 25 afios? Gran canti dad ( 1) Bastante (2) No mucho (3) Paranada (4)
1.5 En su opinion, l,Cuanta influencia pueden tener individuos o grupos sociales en ayudar a mejorar nuestros problemas con el Medio Ambiente? Gran canti dad ( 1) Bastante (2) No mucho (3) Paranada (4)
104 Secci6n 2: Apego a la finca y la practica de cultivo Le voy a leer varias declaraciones y para cada una quiero que Ud. me diga si esta de acuerdo o en desacuerdo. Quiero que me diga si Ud. esta muy de acuerdo, mas o menos de acuerdo, se siente neutral, mas o menos en desacuerdo, o muy en desacuerdo. 2.14 Porque es agricultor?
0 "Cl 0 0 i.. "Cl "Cl Q,I i.. i.. Q,I -; Q,I ~- =y =Q,I i.. =y = ~ .... y .... ~ Q,I =Q,I = ~ = - Q,I"' ~. ~ z r.l= "Cl ~~ 2.1. La agricultura es la labor mas fundamental, todas las 1 2 3 4 5 demits ocupaciones dependen de ella. 2.2. Un problema en la agricultura desencadena problemas en 1 2 3 4 5 el pais entero. 2.3. La practica 105 Secci6n 3: Preguntas Demograficas <<3.1 El genero de la persona _Hombre __Mujer>> 3.2 (,Cuantos aftos tiene usted? __aftos 3.3 (,Grado escolar al que lleg6? Ninguno 0 Primaria incompleto 1 Primaria completo 2 Secundaria incompleto 3 Secundaria completo 4 Universidad completo 5 3.4 (,Especificamente a que actividad agropecuaria se dedica? Agricultura 1 Ganaderia 2 Ambos 3 3.5 (,Cual es el mensual ingreso de la casa? ----mensual 3.6 (,Cuanto de ese ingreso aporta la finca? ----mensual 3.7 Incluso Ud., cuantas personas (adultos y niiios) viven en su casa? 3.8 (,Cual es su tipo principal de transporte? Carro/camioneta 1 Camion 2 Motocicleta 3 Bicicleta 4 Caballo 5 Bus 6 Turi 7 Otro: 8 A pie 9 106 Secci6n 4: Caracteristicas de la fine a Ahora hablemos de la finca y de la tierra que Ud. tiene. 4.1 (.Cuanta tierra tiene, yes duefto o alquila esta tierra? Hectareas 4.1.1 Alquila 4.1.2 Dueno 4.1.3 Otra forma 4.2 (.Cuantas hectareas cultiva en total incluyendo pastos? 4.3 (.Tiene Ud. escritura legal de la tierra? No 0 Si 1 4.4 (.Por cuanto tiempo ha estado esta tierra en manos de su familia? aftos 4.5 (.Ud. recibi6 a esta tierra con la ayuda de alguna organizaci6n del gobiemo? No 0 Si 1 107 Secci6n 5: Relacion con EARTH 5.1 (,Ha escuchado a cerca de la Universidad EARTH? No 0 Continua con seccion 6 Si 1 5 .2 (,Ha hospedado a alg(m estudiante de EARTH para realizar trabajos en su finca? Nunca 0 El aiio pasado 1 Durante los tres aiios pasados 2 Mas de tres aiios atras 3 5.3 (,Ha atendido a alguna reunion u otra actividad organizada por EARTH? No 0 Si 1 5.3.1 (,Cuantas veces durante este aiio? ____ 5 .4 (,Ha estado en el campus de EARTH? No 0 Si 1 5.5 Alguien de su casa esta empleado en la EARTH, ahora o antes? No 0 Si 1 5.5.1 Ahora 1 Antes 2 5.6 (,Como evaluaria el trabajo en la comunidad que hace EARTH? Muy positivo 1 Positivo 2 Neutral 3 Negativo 4 Muy Negativo 5 No quiere responder 9 5.7 (,Cual es el base principal de su opinion? Contacto directo con EARTH 1 Ha conversado con otras personas 2 Feria America Tropical 3 Algll.n material que leyo (;, donde? ______, 4 Television o otros medios de comunicacion 5 Otro (especifique): ______6 5.8 (,Tiene usted algll.n comentario a cerca de su experiencia con EARTH? 108 6.12 (,Ha adoptado otras tecnologias que pueden mejorar el medio ambiente? (por ejemplo, agricultura organica) 6.12.1 l Cuales? 6.12.2 (,Principal fuente de informaci6n? 6.12.3 (,Porque esta usando? Secci6n 7: Biodigestor Si tiene biodigestor 7. I (,Ha tenido problemas con su Biodigestor? No 0 El estiercol se endurece en la bolsa 1 Un hueco en la bolsa 2 Escape de gas 3 No suficiente producci6n de gas 4 Dificil de mantener 5 Otro: 6 ------~ 7.2 (,Ha hecho algunas adaptaciones o cambios a su Biodigestor? No 0 Cambios a las entradas en el BD 1 (,A que? Especificaci6n: ______Cambios a la estructura del BD 2 (,Como? Por favor especificar: ------~ 7.3 (,Utiliza lo que sale del Biodigestor? No 0 Como fertilizante 1 Otro: ------~ 7.4 l Como elementa su Biodigestor? Estiercol de cerdos 1 Estiercol de vacas 2 Suero 3 Otro: 4 ------~ 109 usando econ6micas ecol6gicas ta .i es Ventajas Otro Razones usando I 2 3 Porque 6 esta Porque ventas e d H Veterinario Vecino Representante fuente Ganaderia 5 ...... y EART de informaci6n 10 5 7 ) ultura c de i e? Principal aspecto Agr dond l ( cada de es RTH dej6 EA sobre esor/Jnvestigador or f 4 de usarlo inisterio tailandes publicado M l de ad/Pro - cos Porque (especificar) product i lt eria t nsultor ro tudiante t ecn informaci6n MAG Facu Es Ma T Co O Otro de e t f f Si Sf en S Si Si Si Sf S Sf Sf Sf u I I I I I I I I I I I 3 esta I II 3 F 6 9 8 2 4 No No No No No No No No No No No de escuchado innovaci6n Ha Sf Sf Si Sf Si Si Si Sf Sf Sf Sf finca ha I I I 2 ado la Lo us No No No No/ No/ No/ No/ No/ No/ No/ No/ en ... ~ finca o rl Sf Sf Sf Si Si Si Sf Sf Sf Sf Sf (1) I sa I I I I I I I I 1 I esta necesarios u Esta ahora No No/ No No No No No No usando No/ No No (0) en como trabajo caro o recursos n nd de ecesaria ado e i n especificar) ( descontinuar nti de con sirve tengo e es ermsiado erms ara p D D No Otro No No No Aspecto EM Preparati\Os Biodigestor Bloques Bokashi Compostaje Compostaje Especies Lagunas Plantas Sistema es 1 3 5 2 10 11 6 7 8 9 . . . . . . . . . . I 5 2 3 Razones 6 9 4 nutricionales 6 6 EM 6 6.4 Lombriz Tradicional pee 6 medicinales 6 6 descontaminaci6 conlagunas 6 6 6 agro-ecoturismo 6 forestales 0 ......