FARMERS’ EVALUATION OF AGROFORESTRY TREE SPECIES IN ROBUSTA COFFEE (COFFEA CANEPHORA PIERRE EX FROEHNER) CULTIVATION SYSTEMS IN BUKOMANSIMBI DISTRICT, UGANDA

Fred Kalanzi

A Thesis Submitted in Partial fulfilment of the requirements for the degree of Master of Science (MSc) Tropical Forestry and Management

Faculty of Forest, Geo and Hydro Science Institute of International Forestry and Forest Products Technische Universität Dresden Germany

Supervisor: Dr. Hubertus Pohris Institute of International Forestry and Forest Products TU Dresden, Germany

Co-supervisor: Dr. Klaus Römisch Institute of Forest Growth and Forest Computer Sciences TU Dresden, Germany

Date of Submission: Lending admitted/ not admitted

Chairman of Examination Commission: Dresden, Germany

DECLARATION I hereby declare that this work has never been accepted anywhere for a degree award and is not being concomitantly submitted in candidature for any degree.

Signature: ………………………………

Candidate: Fred Kalanzi

Date: ………………………………

i

DEDICATION This Thesis is dedicated to the spirit of my beloved mother Janet Namiya.

ii

ACKNOWLEDGEMENT This research is a product of many contributions from individuals and institutions. First and foremost, I would like to express my deepest gratitude to my Supervisor Dr. Hubertus Pohris for his wholehearted scientific guidance, encouragement and competent supervision. His unwavering interest in my study gave me intrinsic motivation to be persistent.

I would also like to extend my gratitude to my co-supervisor, Dr. Klaus Römisch for the untiring guidance through the analysis and later stages of my research. His willingness to accept the task of co-supervision of my research abated my fears in the study.

I extend my sincere gratefulness to the management of SCC-Vi Agroforestry Project in Masaka Uganda for their interest in my research and logistical support offered to me during the period of data collection. I‟m particularly deeply indebted to them for their positive criticism and resourceful comments during the early stages of this study. I would like to appreciate very much the warm welcome, friendliness and cooperation from all the staff of SCC-Vi agroforestry project.

I wish to thank my family and friends for their encouragements and support throughout my study. A vote of thanks extends to my colleagues and friends from the Institute of International Forestry and Forest Products who gave valuable comments during formal and informal discussions.

I owe distinguished appreciation to all coffee farming households for their hospitality and sincerity during the workshop, household interviews and coffee farm visits. They willingly spared their scarce time, especially during the intensive rainy period, to share with me their knowledge and experiences.

Finally, I wish to extend my gratitude to Deutscher Akademischer Austausch Dienst (DAAD) for financing the MSc. Tropical Forestry and Management Programme at Technische Universität Dresden.

iii

TABLE OF CONTENTS DECLARATION ...... i

DEDICATION ...... ii

ACKNOWLEDGEMENT ...... iii

TABLE OF CONTENTS ...... iv

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

LIST OF ACRONYMS ...... ix

ABSTRACT ...... x

1. INTRODUCTION ...... 1

1.1 Background...... 1

1.2 Problem statement ...... 2

1.3 Objectives ...... 3

1.3.1 Specific objectives ...... 3

1.3.2 Research questions ...... 3

2. LITERATURE REVIEW AND THEORETICAL FRAMEWORK ...... 4

2.1 Agroforestry research and extension in Uganda ...... 4

2.2 Coffee cultivation systems ...... 5

2.3 Tree species selection for coffee agroforestry ...... 6

2.4 The importance of tree shade on coffee ...... 7

2.5 Effects of trees in coffee agroforestry systems ...... 8

2.5.1 Positive effects ...... 8

2.5.2 Negative effects...... 10

2.6 Tree species suitability for coffee agroforestry ...... 11

2.7 Products from coffee agroforestry systems ...... 12

2.8 The theoretical framework ...... 13

2.8.1 The concept of coffee agroforestry ...... 13

2.8.2 The knowledge gap hypothesis theory ...... 15

iv

3. STUDY AREA, RESEARCH DESIGN AND DATA COLLECTION METHODS ...... 18

3.1 General background ...... 18

3.2 The study area ...... 18

3.3 Research design ...... 20

3.4 Sampling ...... 20

3.6 Data collection methods ...... 21

3.6.1 Secondary and socio-economic data ...... 21

3.6.2 Primary data collection ...... 21

3.7 Data analysis and presentation ...... 25

4. PRESENTATION OF RESULTS ...... 26

4.1 Social and farm characteristics of the coffee farmers ...... 26

4.2 Classification of Coffee agroforestry cultivation systems ...... 27

4.2.1 Classification criteria ...... 27

4.2.2 The Subsistence based cultivation system ...... 28

4.2.3 The Banana-coffee intercropping system ...... 28

4.2.4 The Traditional shaded cultivation system ...... 29

4.2.5 Predicting a given cultivation system ...... 30

4.2.6 Tree species distribution among cultivation systems ...... 32

4.3 Criteria for selecting coffee agroforestry tree species ...... 32

4.4 Major tree species grown on the coffee farms ...... 35

4.5 Uses and main products of trees grown ...... 37

4.6 Farmers’ perceptions on tree species grown ...... 38

4.6.1 Positive effects of trees on coffee ...... 38

4.6.2 Negative effects of trees on coffee ...... 39

4.6.3 Tree species establishment and management ...... 41

5. DISCUSSION OF RESULTS ...... 43

5.1 Classification of Coffee agroforestry cultivation systems ...... 43

5.2 Discriminating between coffee agroforestry cultivation systems ...... 46 v

5.3 Criteria for selecting coffee agroforestry tree species ...... 47

5.4 Major tree species grown on the coffee farms ...... 50

5.5 Farmers’ perceptions on agroforestry tree species grown ...... 53

5.5.1 Positive perceptions ...... 53

5.5.2 Negative effects...... 55

5.6 Tree species establishment and management ...... 57

5.7 The farmers’ ideotype tree specification for coffee agroforestry ...... 57

6. REFLECTIONS, CONCLUSIONS AND RECOMMENDATIONS...... 59

6.1 Reflections ...... 59

6.1.1 Relationship between theory and findings ...... 59

6.1.2 Reflections on research questions ...... 59

6.2 General conclusions ...... 60

6.3 Limitations of the study ...... 61

6.4 Recommendations ...... 62

7. LIST OF REFERENCES ...... 64

8. LIST OF APPENDICES ...... 71

vi

LIST OF TABLES

Table 2.5: Summary of effects of trees on soil ...... 9 Table 4.1: Characteristics of coffee farmers interviewed during the household survey ...... 26 Table 4.2.1: Main coffee agroforestry cultivation systems ...... 27 Table 4.2.2: Relative importance of variables ...... 30 Table 4.2.3: Classification table of the different agroforestry cultivation systems ...... 31 Table 4.2.4: Frequencies of farmers subscribing to a given variable in each cultivation system ...... 32 Table 4.3: Matrix of options and criteria constructed with farmers ...... 35 Table 4.4.1: Trees, their uses and main products according to their overall frequency ...... 36 Table 4.4.2: Pearson’s Chi-square test p-values for tree species against informal education ...... 36 Table 4.6.2: Farmers’ observation of tree negative effects ...... 41 Table 4.6.3: Species establishment and source of planting materials ...... 42 Table 5.4: Summary of the species ecology and uses in Uganda ...... 51

vii

LIST OF FIGURES

Figure 2.8: Conceptual framework of the research project ...... 14 Figure 3.2: Location of the study area ...... 19 Figure 3.6.2: Primary data collection ...... 22 Figure 4.3.1: Criteria and indicators used to select trees used in coffee agroforestry systems ...... 33 Figure 4.3.2: Most important selection criteria from the household survey ...... 34 Figure 4.5: Farmers’ desired tree species for enriching coffee fields ...... 37 Figure 4.6.1: Positive effects of agroforestry trees on coffee ...... 38 Figure 4.6.2: Farmers’ opinion on negative effects of trees on coffee ...... 40 Figure 5.2: A hypothetical pathway to predict an agroforestry cultivation system ...... 46 Figure 5.6: An ideotype tree specification for coffee agroforestry in Bukomansimbi ...... 58

viii

LIST OF ACRONYMS CAB Centre for Agricultural Bioscience CORI Coffee Research Institute CWD Coffee Wilt Disease D&D Diagnostic and Design FAO Food and Agriculture Organization FORRI Forestry Resources Research Institute ICRAF International Council for Research in Agroforestry LWF Lutheran World Federation MADDO Masaka Diocesan Development Organization NAADS National Agricultural Advisory Services NGOs Non Governmental Organizations PEAP Poverty Eradication Action Plan PMA Plan for Modernization of Agriculture SCC Swedish Cooperative Centre UBOS Uganda Bureau of Statistics UCDA Uganda Coffee Development Authority

ix

ABSTRACT The main objectives of this study can be summarized as: classification of Robusta coffee cultivation systems, understanding the criteria used by farmers in coffee agroforestry tree species selection, and assessing farmers‟ perceptions on the main tree species grown in coffee agroforestry systems. The field work was conducted from March to June, 2011 in Bukomansimbi district, Uganda. The study area experiences a bimodal rainfall pattern and rainfall ranges between 1200 – 2000 mm.

The study followed a survey research approach and 72 coffee farmers were interviewed using a semi-structured household survey questionnaire. A snow ball sampling method was used to identify the sample. Other primary data collection methods used were key informant interviews, a coffee farmers workshop and on-farm observations. Statistical data analysis involved the use of descriptive and inferential analytical techniques. Cross tabulation analyses using chi-square tests (P < 0.05) to determine statistical independence between variables were carried out.

The main agroforestry cultivation systems classified in the area were: Subsistence based cultivation system, the Banana-coffee intercropping system and the Tradition shaded coffee cultivation system. Formal education, fertilizer input, informal education, and land size were the main socio-economic variables found to discriminate between these systems. The criteria and indicators considered by farmers during tree species selection were characterized into primary and secondary criteria. Primary criteria included optimal shading habits, addition of nutrients to the soil and product diversification. Secondary criteria included strong anchorage, less labor intensiveness, attraction of pollinators, and non-hazardousness.

Tree species diversity in coffee agroforestry systems was generally low. Only 16 tree species were found to be grown with coffee in the area with the top five being Ficus natalensis, Artocarpus heterophyllus, Maesopsis eminii, Mangifera indica, Persea americana. However, some of these also reported some negative effects on coffee such as resource competition, over-shading, aiding pests and diseases as well as physical damage. Yet despite these negative effects, they were still generally maintained in coffee because of additional uses that they provided. This research work proposes an ideal tree species model for coffee agro forestry based on the point of view of the farmers in Bukomansimbi. This model can guide extension agents to plan their interventions in the area. More research is also needed to understand the interaction between coffee and the most grown tree species in the area.

x

CHAPTER 1

INTRODUCTION

1.1 Background

Coffee plays a leading role in the economy of Uganda contributing between 20-30% of the foreign exchange earnings (UCDA, 2010) and over 60 % of the total value added of cash crops (Government of Uganda, 2010). The two coffee species Coffea canephora and Coffea arabica, predominantly known as „Robusta‟ and „Arabica‟ coffee respectively, are grown in a ratio of 4:1 with Robusta being favored in the low altitude area while Arabica is restricted to highland areas. Because most of Uganda is low land, Robusta coffee, which is also native to the Lake Victoria crescent, is the most widely grown coffee. Although it‟s believed to be lower in quality than Arabica coffee, Robusta coffee is reported to have a relatively high pest and disease resistance (Klein et al., 2002).

Coffee production has been facing a global crisis due to overproduction and persistently low prices (Soto-Pinto et al., 2007). Ugandan coffee in particular had lagged behind with regard to international quality standards. This prompted the establishment of UCDA in 1991 to make Uganda a distinguished producer of high quality coffee. The coffee sector was unfortunately hit by the CWD1 (Tracheomycosis) which reduced the production levels tremendously. Thus a lot of research by CORI has been in development of disease resistant varieties, disease identification and control.

Traditionally, coffee is grown under shade trees (Klein et al., 2002) but some forces, mainly economic and ecological, are shaping the way coffee is being grown worldwide. In economic terms, there is an increasing demand for coffee, shifting the attention of coffee producing countries towards increased yields. In Mexico for instance, there was a shift from more diverse cultivation systems towards monocultures in order to achieve higher coffee yields (Romero-Alvarado et al., 2002). Ecologically, the need to ameliorate adverse climatic conditions as well as meet the demands of „green consumers‟ has meant more use of shade trees in coffee production systems (Beer et al., 1998; Albertin and Nair, 2004).

Coffee farmers in Uganda have traditionally grown trees in their coffee in what has now come to be known as agroforestry. Such trees would also widen the spectrum of products and services from the coffee farms. In order to balance both ecological and economic objectives pressing in the current times, trees for growing in coffee need to be carefully selected. While

1 CWD resurged to become the principle production obstacle for Robusta coffee in Uganda in 1990s. It’s of special significance because unlike other major diseases such as coffee leaf rust (Hemileia vastatrix) and coffee berry disease (Colletotrichum kahawae), it kills the coffee tree. 1 it‟s difficult to optimize the selection of agroforestry tree species (van Oijen et al., 2010), researchers point to a higher involvement of farmers in research and extension programmes (Sinclair and Walker, 1998; Soto-Pinto et al., 2007). It is argued that farmers‟ experience and knowledge is certainly becoming essential in designing agroforestry systems that are both ecologically and economically viable (Grossman, 2003; Soto-Pinto et al., 2007).

1.2 Problem statement

A high “diversity of agroforestry…” is reported as one of the characteristics of humid tropics (Nair, 1993: 46). No wonder, there is a variety of tree species found growing in the tropics most of which have insufficient scientific information. In terms of agroforestry, this tree species diversity presents a challenge during the selection of tree species for agroforestry systems (Souza et al., 2010).

In Uganda, and perhaps elsewhere, coffee is amenable to tree growing. Coffee agroforestry systems are believed to play a number of productive and service functions (Sinclair and Laxman, 2000; Soto-Pinto et al., 2007). Yet despite a number of policies such as PEAP, PMA, the National Forest Policy, and the National Forest Plan; all in support of wide-scale promotion of agroforestry in the country, Coffee agroforestry has received little attention.

Despite a number of benefits agroforestry trees provide to farmers (Soto-Pinto et al., 2007, Snelder and Lasco, 2008), much of the coffee research in Uganda has centered on development of technologies for improving agronomic and quality performance (UCDA, 2009). Some of the tree species promoted by research and development organizations for coffee agroforestry are not based on genuine research and farmers‟ needs, knowledge and experiences. This challenges the popular belief that the success of agroforestry system is based on ensuring that farmers are interested in the tree species being promoted (Souza et al., 2010).

It is generally accepted that agroforestry is a new terminology for old practices since farmers have been growing trees on their farms for generations. It is believed that farmers have lots knowledge about grown tree species. This rich knowledge-base has evolved overtime through hands on experience. Unfortunately most of the times they are passive participants in research development.

Unearthing the knowledge of farmers‟ evaluation of agroforestry tree species, especially in Bukomansimbi district where farmers have considerable experience and knowledge about tree species found growing in their coffee fields, can be a milestone to both scientists and extension agents. It‟s an opportunity to establish research priorities concerning promising

2 tree species for promotion in coffee agroforestry systems. It‟s a basis for promotion of ecologically sound, economically acceptable and socially complaint agroforestry tree species for coffee agroforestry.

1.3 Objectives

The main objective of the study is to contribute to a thorough understanding of the evaluation of agroforestry trees in Robusta coffee cultivation systems from the farmers‟ perspective, and to suggest ways for better promotion and dissemination of coffee agroforestry tree species.

1.3.1 Specific objectives

The specific objectives are:

 To classify the main Robusta coffee cultivation systems in Bukomansimbi district  To determine farmers‟ criteria for selecting agroforestry tree species to incorporate in coffee farms;  To determine farmers‟ perceptions of the main agroforestry tree species grown and their interactions with the coffee plants;  To identify options for future research and extension interventions.

1.3.2 Research questions

Classification of Robusta coffee cultivation systems

 Is there a set of variables which can be used to predict a given coffee agroforestry cultivation system?

Farmers‟ criteria for selecting agroforestry tree species

 What are the main tree species grown with coffee and why are they selected for coffee agroforestry?  What tree attributes and respective indicators do farmers consider for tree species grown on coffee farms?

Farmers‟ perceptions of the main agro forestry tree species grown

 What are the limitations of the main tree species being grown on coffee farms?

3

CHAPTER 2

LITERATURE REVIEW AND THEORETICAL FRAMEWORK

2.1 Agroforestry research and extension in Uganda

The development of new technologies in earlier decades was attributed to the conventional approach of on-station research. A strong commitment to on-farm research has been noted in recent times (Muschler and Bonnemann, 1997; Franzel et al., 2001) and its ability to bridge the gap between research and practice stressed (Muschler and Bonnemann, 1997). However, despite the on-farm research intensification, the case of Uganda is that of farmers being passive participants who simply test new technologies without being consulted in generating them.

Owing to the enormous role that agroforestry can play in the country for food, wood security and conservation of the environment, agroforestry research was put on agenda with the formation of the National Forestry Resources Research Institute in 1993. The programme was mandated to conduct on-station and on-farm research. Much of the emphasis to-date has been on-station research yet conditions under which the majority of farmers operate differ significantly from those at the research stations. Consequently, unless special attention is paid to farmers‟ conditions during research, the resulting technologies may be inappropriate to the majority of the farmers (Raintree, 1983). Nevertheless a number of tree species such as Grevellia robusta, Cedrela serrata, Casuarina spp. and Markhamia lutea have been screened and promoted for boundary planting and intercropping for low and mid altitudes areas.

Based on the traditional model (Compton, 1984) the original concept of extension was that of bridging the gap between the farmers and organizations or institutions generating knowledge and technologies. In fact, in developing countries it is the primary mechanism used to assist farmers in expanding their knowledge base. However, in Uganda, extension programmes have been criticized for being largely ineffective and adding very little to the productivity of farmers. A good example is the government‟s suspension of the NAADS programme in 2007 on the ground of implementation failures.

As Evenson (1997) points out, the large variation in programme design and field work skills limits the feasibility to make broad generalizations about the contribution of extension. Past research has unearthed relationships between farm size and factors of production. Large farms are more likely to use advanced farming inputs such as fertilizers and improved varieties (Reed, 2007). This has led many agricultural programmes to focus more on larger more refined farms that are viewed as better equipped to adopt new technologies.

4

2.2 Coffee cultivation systems

All over the world, coffee production has taken on a great variety of forms and designs which make it complicated to device a single typology of coffee cultivation systems. To avoid this difficulty, some researchers have simply grouped coffee cultivation systems into shaded and unshaded coffee (e.g. Nestel, 1995; Amoah et al., 1997; Muschler, 1997; Beer et al., 1998; DaMatta, 2004). Other researchers have nevertheless developed some criteria to classify further the cultivation systems. For example, Moguel and Toledo (1999) described five different common coffee production systems in Mexico, ranging from traditional smallholdings by native trees to larger full-sun systems relying on chemical inputs and year round-labor. Their classification was based on management level and vegetation and structural complexity. López-Gómez et al. (2008) classified three systems based on vegetation structure and species richness in Veracruz, Mexico.

In Uganda, coffee has been grown by farmers for a number of generations. While there is no comprehensive study on the different cultivation systems, it is generally accepted that coffee cultivation systems have evolved over time. Originally, coffee farming was done under the shade trees that provided a habitat for many animals and insects. Most of these trees were remnant forest trees but many other trees relevant to the needs of the farmer could also be planted. This system is here referred to as the “traditional shaded” cultivation system.

During the colonial era, Ugandan coffee was open to the external market in United Kingdom. The colonial chiefs emphasized production of coffee and cotton on a large scale. There was increased demand and emergency of mechanization which led to coffee monocultures. These monocultures generally required intensive fertilizer applications to optimize productivity. Consequently, they were liable to environmental degradation (DaMatta, 2004).

An earlier study in Uganda by Oduol and Aluma (1990) documented the Banana (Musa spp.) – Robusta coffee cultivation system in which coffee serves as a cash crop and banana as a food crop with a variety of trees in the system. This system is practiced in the banana coffee zone2 and it is believed to have risen to prominence after massive clearance of the ever green forests especially in 1970s (Oluka-Akileng et al. 2000). This crop combination was based on banana as the main food crop and Robusta coffee as the main cash crop but with

2 The banana-coffee zone is a terminology describing one of Uganda’s six agro-ecological zones (Aluka-Akileng, et al. 2000). It occupies the largest area and dominates most of the southern region of the country. It is dominated by coffee as the main cash crop and banana (Musa spp.) as the main food crop.

5 both crops contributing to the final household income (ibid). The system also involves planting or retaining of multipurpose trees for services and products of both subsistence and commercial value. Oduol and Aluma (1990: 219) documented some of the trees and shrubs suitable for this system which according to them was predominantly a homegarden practice.

This study focuses on coffee agroforestry and will seek to explore shaded plantations. Coffee agroforestry in totality according to (DaMatta, 2004), seeks to conserve natural resources, supplement more income to the farm households and diversify products for domestic consumption.

2.3 Tree species selection for coffee agroforestry

Agroforestry deals with a heterogeneous clientele of farmers with differing needs (Franzel et al., 1996). The selection of appropriate tree species is essential to the success of an agroforestry system. It should follow both the environmental needs and priority needs of the farmer (Souza et al., 2010). In other words, tree species selected should match the farmers‟ needs and the needs of their particular farming systems and agro-ecological conditions. This makes it difficult for a standard tree selection procedure to be implemented in practice since a single tree species provides some but not all of these products and services.

Nair (1993: 16) proposes that tree selection must be based on “…productivity, sustainability and adoptability” for agroforestry to be meaningful to farmers. In terms of productivity, tree species selected must improve production of preferred commodities; the sustainability attributes which mainly refer to the stability of the agroforestry system; while adoptability refers to acceptance of promoted tree species by farmers.

The potential of agroforestry as an approach can only be realized if appropriate agroforestry practices are matched with specific land use situations. The selection and design of agroforestry technologies for specific land use systems emerge from the D&D methodology (Raintree, 1989). The D&D methodology was developed to help identify research goals for sound development of agroforestry technological interventions.

Based on the fact that the D&D design could clarify the role and function of any required tree species, von Carlowitz (1989) demonstrated the process of candidate multipurpose tree species (Figure 2.3) with the aim of focusing further research on trees most likely to succeed in a given agro-ecological zone. The tree uses and characteristics which are relevant to a specific function are expressed in terms of standard descriptors which can be used, in combination with climate and soil parameters to select for candidate species. For each parameters, desirable qualities are ranked in order of importance and from 6 such an embracing string of concurrent conditions, only those species emerge which match an unbroken and complete combination of all the specified conditions.

Figure 2.3: Preselection of tree species for specific agroforestry technologies (von Carlowitz, 1989)

Although von Carlowitz (1989) emphasized the use of a scientifically based rationale in identifying production objectives that form a basis of the selection, the fact is that farmers have been planting trees for generations. Through their experience, they might have developed an informal set of criteria which is simple and problem based.

There has been an attempt to document farmers‟ criteria for tree species selection. In his study on the selection of native trees for intercropping with coffee in the Atlantic Rainforest biome, Souza et al. (2010) unveiled a set of criteria used by farmers. These criteria were similar amongst farmers but they would still result in selection of different tree species (ibid: 13). In general, tree species selection is highly influenced by the farmer‟s objectives and constraints, the individual tree attributes and the nature of the system in which they are to be grown (Huxley, 1999). Besides, tree species selection criteria may differ among farming communities operating in different ecological zones. Therefore any investigation that focuses on the farmers‟ perspective reveals interesting findings to both academia and practitioners.

2.4 The importance of tree shade on coffee

The effects of shade on coffee have been widely documented (Amoah et al., 1997; Muschler, 1997; Beer et al., 1998; DaMatta, 2004). Shaded coffee may decrease or maintain the yield depending on the quality of shade. Soto-Pinto et al. (2000) found out in Chiapas Mexico that shade cover percentage had significant effects on coffee yields and that production 7 decreased under shade cover of over 50%. One of the reasons advanced for this is that excessive shade reduces the whole-tree carbon assimilation while stimulating vegetative rather than flower buds (DaMatta, 2004). But it‟s also argued that shaded coffee tends to produce good crop each year owing to reduced overbearing and buffered biennial fluctuations offered by the tree shelter (ibid).

The decision by the farmer to use shade trees cuts across stability and productivity. Farmers will favor shade trees if they are interested in stabilizing production through environmental services such as microclimate amelioration, fertility, and erosion control while at the same time obtaining extra products from the trees (DaMatta, 2004).

In his empirical model for Arabica coffee, Muschler (1997) argues that coffee production is evaluated as a function of altitudes. In soils without limitations to rooting depth, nutrients or moisture, maximum coffee production would occur under unshaded conditions. Outside these range, he notes that the use of shade trees would buffer microclimatic extremes and improve over that of monoculture plantations as long as the crop competition for water and nutrients is not excessive. While this model may seem true for Arabica coffee which is often grown at high altitudes, it falls short of low land areas where Robusta coffee is grown. Thus it cannot be applicable to Robusta coffee production.

However, DaMatta (2004) points out that in regions with lower altitudes characterized by warmer temperatures and prolonged unpredictable droughts, shading is promising for coffee. Amoah et al. (1997) found a positive correlation between shade intensity and maximization of yield as the environmental conditions become less favorable for Robusta coffee cultivation. It is reported that the highest yield of Robusta coffee occurs in full sun conditions and that this requires a lot of fertilizer application to sustain production (Rehm and Espig, 1991). However, under unfavorable conditions, shade moderates the microclimatic conditions and helps to sustain yields. It is thus probable that the less favorable a site becomes as a result of environmental and edaphic stresses, the greater would be the shading benefits to coffee (DaMatta, 2004).

2.5 Effects of trees in coffee agroforestry systems

2.5.1 Positive effects

The selection and management of shade trees for coffee agroforestry can bear several positive and negative effects on coffee plants. A number of benefits have been put forward to elucidate the importance of trees in coffee agroforestry systems (Beer, 1987; Beer et al., 1998). These benefits can be categorized in many ways.

8

For simplicity, Beer et al. (1998: 141) highlight physiological benefits as one of the categories and group these into two categories: 1. Amelioration of climatic and site conditions through; (i) reduction of air and soil temperature extremes, (ii) reduction of wind speeds, (iii) buffering of humidity and soil moisture availability (iv) improving or maintenance of soil fertility including erosion reduction; and 2. Reduction in the quantity and quality of transmitted light and hence avoidance of over-bearing and/or excessive vegetative growth.

Table 2.5: Summary of effects of trees on soil BENEFICIAL EFFECTS Nature of processes Processes/avenues Main effects on the soil

INPUT (Augment additions to soil) Biomass production (litter and Improvement or maintenance of root decay) organic matter

Nitrogen fixation N-enhancement

Effects on rainfall (quality and Influence of nutrient addition distribution through rain/dust

OUTPUT Protection against water and Reduce loss of soil and (Reduce losses from soil) wind erosion nutrients

TURN-OVER Nutrient retrieval/cycling/release Uptake from deeper layers and deposition on surface

Withholding nutrients that can be lost by leaching

Timing of nutrient release

“CATALYTIC” Physical Improvement of soil properties (Indirect influences) Chemical Moderating effects on acidity, salinity and alkalinity

Microclimatic Ameliorative effect on extreme conditions

Effects on soil microorganisms; Biological improvement of litter quality through species diversity ADVERSE EFFECTS 1. Competition for water and nutrients 2. Production of growth inhibiting 3. Loss of nutrients through tree harvesting 4. Possible adverse effects on soil erosion Source: Nair (1993:270) (Adapted from Nair, 1989 and Young, 1989) 9

Trees are also known to offer agronomic benefits. Trees add organic matter to the soil as a result of litter fall and help to reduce environmental stresses. Leguminous trees replenish the soil through nitrogen fixation. However some studies have revealed that the quantity of nitrogen fixed by leguminous trees is generally low (Fassbender, 1987). The ability of the tree to produce large quantities of organic matter, as litter and pruning residues is rather more important than nitrogen fixation because of the positive effects on the soil‟s chemical and physical properties (Beer et al., 1998). In addition to its use in managing the microclimate of the underlying coffee, pruning has a critical influence on nutrient cycling. It provides a tool to manipulate the timing and quantity of nutrient transfer from tree to soil (Beer et al., 1998). Tree shade also reduces the quantity and quality of light reaching the coffee plants which helps avoid overbearing and excessive vegetative growth (ibid). The overall effect is relieved stress on the coffee plants, affording shaded coffee increased longevity over unshaded coffee. Moreover the reduced dieback and overbearing allows for a more consistent harvest from each individual coffee tree.

If shade trees are to contribute to erosion control, natural litter-fall and pruning residues should maintain a mulch layer during the rainy season (Beer at al., 1998). In this respect, slow litter decomposition would be an advantage. While a dense shade canopy would provide better soil protection than an open canopy during high intensity rainfall, it could also adversely lead to increased surface erosion. Hence, a low crown with small leaves is preferable to minimize chances of erosion (Beer et al., 1998).

Income from shade trees like fruits, timber, firewood and other tree products has been reported to be significant (Somarriba, 1992; Soto-Pinto et al., 2007; Snelder and Lasco, 2008). Such products can supplement the total income from the coffee farm. Additionally, some of these products can be used to meet household subsistence needs.

2.5.2 Negative effects

The negative effects are also well elucidated in the publications of Beer (1987), Somarriba, (1992) and Beer et al. (1998). The major drawback to growing trees in coffee is the competition for nutrients and water between the coffee and shade trees. This leads to a drastic reduction in yield if the coffee is shaded too heavily. A reduction in the amount of sunlight reaching the coffee leaves results in low photosynthetic rates and inhibits other plant activities such as fruiting. Moreover the amount of shading was found to have an inverse relationship to coffee stem counts in the natural coffee forests of Bonga in southwestern Ethiopia (Muleta et al., 2007).

10

There is a lack of agreement among farmers and scientists as to whether shade trees reduce or increase diseases and pests of economic importance. Excessive shade can provide favorable moist conditions for the infestation of economically important fungal diseases. However, an injudicious choice of tree species could have the opposite effect. Inga spp. for example have been found as alternative hosts for coffee nematodes in Costa Rica (Zamora and Soto, 1976: In Beer et al., 1998).

During the harvest of tree products especially timber, coffee plants can be damaged (Somarriba, 1992). This leads to decreased coffee yields. Despite possible coffee damage, Beer et al. (1998: 154) argue that the low restoration costs of affected plants, the small reductions in coffee yields and the large financial gain from timber sales strongly support the use of trees in coffee plantations.

2.6 Tree species suitability for coffee agroforestry

Tree species‟ characteristics will largely determine whether tree-coffee interaction is detrimental or beneficial to the components and the system (Beer, 1987). A number of characteristics important for shade tree species are published by Purseglove (1968) and Beer (1987: 8) and they include the following: Compatibility

 Minimal competition for resources especially below ground resources such as water and nutrients  Light and widespread crown that provides a regular mottled shade pattern  No allelopathetic properties to coffee plants  Not an alternative host to insects and pathogens which damage coffee  A small diameter light crown to; (1) minimize wind resistance of foliage and hence the risk of wind throw (2) permit relatively high shade tree densities without reducing light levels below critical values for the coffee (3) minimize crop damage when individual trees are harvested  Should not have the capacity to turn weedy such as Leucaena leucocephala in certain areas  Rapid apical growth

Productivity

 Provide valuable tree products such as wood, fruit, timber  In case of timber tree species, they should be self pruning and able to form a straight unforked stem in open crown conditions  Quick growing

11

Stability

 Strong rooting system for adaptation to open-grown conditions (not susceptible to wind throw)  Capable of vegetative propagation  If deciduous, rapid flushing of new leaves to regenerate the shade cover  Tolerance to repeated heavy pruning or pollarding  Absence of major disease or insect susceptibility which could lead to sudden defoliation  Sprouting ability

Sustainability

 Preferably nitrogen fixing  High biomass productivity of materials that is recycled, through leaf-fall and/or pruning, readily decomposed leaves and woody material  Deep roots to recycle nutrients from deeper layers of the soil not available to coffee  Small leaves which decompose rapidly and minimize rain drop coalescence and subsequent drip damage  Long lived to outlast the coffee plants

2.7 Products from coffee agroforestry systems

As much as it is a very lucrative enterprise, coffee production just like other agricultural enterprises, is susceptible to risks. The global coffee market is often chaotic with prices often fluctuating while the cost of agrochemicals required for modern coffee production is high (Lyngbaek et al., 2001). Consequently, production diversity can be considered a reasonable undertaking especially for smallholder families.

Numerous studies have endorsed the importance of coffee agroforestry systems for farmers in provision of marketable and domestic products such as firewood, timber, fodder and fruits (Somarriba, 1992; Peeters et al., 2003; Rice, 2008; Rice, 2011). Wood products in particular, such as timber and firewood, have received much research emphasis. Rice (2008) found out in Guatemala and Peru that non-coffee products account for up to a third of the total value realized from the coffee agroforestry system. He noted fuel wood and construction materials as being the main products. Coffee agroforestry systems in particular provided significant amount of fuel wood in the remote rural settings of Peru and Guatemala.

Peeters et al. (2003) stress that secondary production from trees makes coffee agroforestry systems much more valuable than unshaded plantations. The drop in coffee yield can be

12 compensated for by the tree products. Moreover with wide spacing and sufficient pruning, coffee yield may not be greatly affected (Peeters et al., 2003). Additionally, the marketable options offered by trees can offset farmers‟ reliance on coffee sales and increase their economic stability (ibid).

While assessing the financial benefits of including timber trees, particularly Cordia alliodora, into coffee agroforestry, Somarriba (1992) found out that it could be a viable business particularly when market prices for coffee are low. One of the concerns from the farmers could be that timber trees often grow to reach significant heights thereby causing enormous damage to coffee during timber harvesting. However, Somarriba (1992) recommends that crop damage to tree felling should not downplay the use of timber trees in coffee agroforestry systems more so in situations of both increasing trends in timber prices and fluctuating prices for coffee.

The importance of fruits in coffee agroforestry systems cannot be underscored given that they can contribute to food and income. Rice (2011) noted that Peruvian farmers consume more of the fruits obtained from coffee agroforestry systems as opposed to their Guatemalan counterparts who generate value through sales. He generally noted that fruits from coffee agroforestry systems can make a significant economic contribution to the general output from the coffee farm.

2.8 The theoretical framework

2.8.1 The concept of coffee agroforestry

To assess farmers‟ evaluation of agroforestry tree species in Robusta coffee cultivation systems, this study was guided by a conceptual framework (Figure 2.8) with the coffee agroforestry farm as a fundamental component. The farm can evolve endogenously through farmer‟s indigenous knowledge and household resources or exogenously through interventions from research institutions and change agents. Meanwhile, agroforestry research should supposedly be based on research gaps arising out of the farmers‟ indigenous knowledge and experience.

In making a decision about which tree species to grow, a farmer evaluates first his capacity (endogenous factors) and then opportunities surrounding him (exogenous factors). External services and influences can greatly influence the decision making criteria of the farmers. For instance extension agents can greatly provide high psychological motivations and resource subsidies to grow certain crops. Such factors are evaluated by the farmer before a decision is made on which tree species to plant in the coffee field.

13

Whereas it has been mentioned that farmers are rational decision markers with extensive knowledge about their environment (Raintree, 1983), it is also true that farmers judge alternatives in the face of many risks, uncertainties and multiple objectives and it‟s expected that they make non-rational decisions. Ellis (1993) observes that farmers attempt to achieve various goals simultaneously. Such goals may include securing adequate food supply and essential subsistence goods for family which may sometimes surpass income maximization.

While growing agroforestry tree species, it should not be assumed that economic returns may be the overriding aspect. The situation in developing countries, Uganda inclusive, suggests that subsistence consumption is an important consideration (Senkondo, 2000). Besides maximizing coffee production, the farmer might have other objectives such as diversification for risk management, food for domestic consumption, fodder for livestock, etc. Farmers feel much more secure to balance a variety of needs and goals than to focus on productivity of one crop. Thus the decision on which trees the farmer selects to grow is a convoluted array of interconnected considerations.

Figure 2.8: Conceptual framework of the research project (Source: Own elaboration based on McGregor et al. (2001).

14

2.8.2 The knowledge gap hypothesis theory

The Knowledge Gap Hypothesis (Tichenor et al., 1970) implies that as the infusion of mass media information into a social system increases, segments of the population with higher socio-economic status tend to acquire this information at a faster rate than the lower status segments, so that the gap in knowledge between these two segments tend to increase rather than decrease. The hypothesis predicts that people of both high and low socio-economic statuses will gain in knowledge because of the additional information, but that persons of higher socioeconomic status will gain more and translate this knowledge into practice. The central concern of the knowledge gap hypothesis theory is that knowledge of use of adopted technologies is greater for those with higher socio-economic status and those already well informed.

Although the theory was first applied in the mass media flow research, its pillars are quite vivid to be applied elsewhere in natural sciences including agroforestry. For example, farmers‟ skepticism about certain agroforestry systems may be largely related to their imperfect knowledge of these systems and their socio-economic situations which make them risk averse.

Agroforestry processes can be affected by socio-economic factors (Neupane et al., 2002). The knowledge regarding the usage of improved agroforestry technologies is higher for those with higher socio-economic status and who are well informed. Consequently in a given setting, farmers with a higher social economic class are much likely to posses better managed agroforestry systems. In case of coffee cultivation systems, it means that farmers can adapt to better cultivation systems if they are endowed with motivational socio-economic variables. Thus the testable proposition for this theory is that:

The implementation of a better managed coffee cultivation system is positively related to the improvement in a defined set of socio-economic variables. Reed (2007) and Marenya and Barrett (2007) propose some of these socio-economic variables important in agroforestry which include among others formal education, informal education, and land size.

Formal education Farmers with weak education tend to exhibit high levels of risk aversion compared to their educated counterparts. A higher education level may improve one‟s ability to capitalize on opportunities. Educated people have better abilities to gain information, conceptualize information and discuss topics with other people (Tichenor et al., 1970; Murenya and Barrett, 2007). Blaug (1970: 47) adds that “the better educated are generally more flexible and more motivated, adapt themselves more easily to changing circumstances, benefit more from work 15 experience and training, are more productive than the less educated even when their education has taught them no specific skills”. Therefore, such individuals are more likely to adopt better production systems (Rogers, 2003).

Murage et al. (2011) found out that compared to farmers who had no formal education, farmers with primary education where likely to adopt faster followed by those with secondary education and those with post-secondary education. This is because education allows farmers to obtain clear information and to comprehend and make better decisions. Agroforestry practices are knowledge intensive and require considerable management skills. Formal education signifies latent managerial skills and greater cognitive capacity (Murenya and Barrett, 2007)

Informal education Most agroforestry practices are passed on to the farmers through extension and other informal sources of education. Kuntashula and Mafongoya (2005) found out in Zambia that the influence of informal education on agroforestry was very important in helping farmers to make decisions. Informal education can supplement the deficit in formal education (Marenya and Barrett, 2007; Muneer, 2008) and its influence becomes even much higher in combination with formal education.

While everyone in the community may have an opportunity to access informal sources of knowledge, the expansion of this knowledge is relatively greater for the most educated thus widening the gap between those who are highly educated and those with low education. Informal education like extension education appears to make farmers aware of the profits to be found through the various production systems (Shuck et al., 2002). This is why Rogers (2003) believes that contact with extension staff is likely to increases adoption of new agroforestry technologies.

Land size The diffusion of innovations theory suggests that new innovations are initially adopted by those with more resources (Rogers, 2003). Land is the most important resource in agroforestry. The induced innovation hypothesis (Hayami and Ruttan (1985) suggests that farmers cope with reduced availability of land by adopting technologies that are more suited. The choice of cropping systems by farmers is often a function of farm size (Shuck et al., 2002).

Some agroforestry systems demand a lot of land and their adoption is likely to be influenced by the total farm size operated by the household (Murenya and Barrett, 2007). Shuck et al.

16

(2002) note that a higher level of cultivatable acreage promotes adoption of higher profitability production methods. A big farm size allows a farmer an option to fragment his land according to the enterprises on the farm there by affording specific management practices (Murenya and Barrett, 2007).

17

CHAPTER 3

STUDY AREA, RESEARCH DESIGN AND DATA COLLECTION METHODS

3.1 General background

Uganda is a land locked country within East Africa which is located across the equator, about 800 kilometers inland from the Indian Ocean. It lies between 10 29‟ South and 40 12‟ North latitude, 290 34‟ East and 350 0‟ East longitude (UBOS, 2007). The country covers an area of about 241,038 square kilometers of which the land area covers 197,323 square kilometers. The total population is about 32 million people (Government of Uganda, 2010) with the population growth rate estimated at 3.3% per year (FAO, 2009). The Ugandan population is predominantly rural with the highest population density in the southern regions. Dubbed as the „Pearl of Africa‟ by early European explorers, Uganda has approximately 4.9 million hectares of forests and woodlots (Government of Uganda, 2002).

The country is divided into six distinct agro-ecological zones, namely: banana-coffee zone, montane system, cattle corridor, cereals based systems and pure pastoral system. Agriculture is the main economic activity with coffee and cotton as the dominant cash crops and banana and maize as the main food crops. The coffee sector plays an important role in the economy of the country contributing 25% of the total foreign exchange earnings (UCDA, 2009).

3.2 The study area

This study was carried out in Bukomansimbi district (Figure 3.2) which was formally part of Masaka district before being split off into an independent district on 1st July, 2010. The coordinates of Bukomansimbi district are 00 10S, 31 39E. The population density in the study area is 248 persons per km2 (UBOS, 2007). Agriculture is the foremost economic activity with coffee and Matooke (plantains/banana) being the main cash crop and food crop respectively.

Bukomansimbi district is located in the banana-coffee agro-ecological zone. The district has quite a low variation in topography and the soils are generally characterized by clay loams and sandy loams. The district has a semi-humid type of climate. The rainfall pattern is bimodal with the 1st season from March to May and the 2nd season from September to December. The rainfall ranges from 1200 – 2000 mm. The maximum temperature recorded is 30oC and the minimum 10oC having almost equal lengths of day and night throughout the year.

In terms of agroforestry and tree-related practices, the district has been targeted by a number of programmes. Several NGOs, CBOs and government programmes have promoted 18 agroforestry or some sort of tree planting in the study area. These include among others SCC-Vi Agroforestry Project which worked in the study area for 15 years until 2008, Caritus MADDO, LWF, Ibero Uganda currently operating as Hanns R. Neumann Stiftung, and NAADS. Some of these organizations helped farmers‟ to access tree species, including exotics, which would have been difficult to access. For instance SCC-Vi Agroforestry Project had a long list of tree species that it had promoted in the area (see Appendix 2).

Figure 3.2: Location of the study area (Source: Adapted from http://www.worldatlas.com; SCC-Vi agroforestry Project database)

The study area was selected because of a number of reasons:  The area has a relative homogeneity in topography and agro-climatic conditions. This eliminates from the analysis the variation caused by biophysical and climatic factors.  Its location in Lake Victoria crescent in which Robusta coffee is indigenous. It was believed that farmers in the area have long tradition of Robusta coffee growing. This must come along with practical based experiences and knowledge systems.  The study area is also one of the major coffee producing areas in the country. Consequently, study findings can contribute to future research and extension efforts in the area where most of the people rely on coffee for income.  The district has had a number of NGOs promoting agroforestry and government programmes aimed at improving coffee production. This presented an opportunity to coffee farmers to modify their coffee systems for better productivity.

19

3.3 Research design

A survey research approach (Bryman, 2008) was used for this study. Fresco et al. (1994) argue that the accuracy and reliability of survey results are attributed to the depth rather than the coverage at which they are conducted. To pledge to this premise, field surveys were carried out in phases.

The first phase involved a reconnaissance survey in which the researcher was introduced to the local leaders and the timeframe for data collection was communicated. The importance of such informal meetings is emphasized especially in acquiring support and erasing natural suspicion (Freudenthal and Narrowe, 1991). Unstructured questionnaires designed for key informants interviews (see Appendix 2, B) were used to acquire a deeper understanding into the subject in relation to the study area. This work was instrumental in sharpening the sampling ideas for the main household survey.

The second phase was that of the household survey. In order to ensure validity of the collected data, a semi-structured questionnaire was developed and pretested using 6 randomly selected coffee farmers. Necessary modifications were made and the final questionnaire (see Appendix 2, A) was administered by the researcher himself since there was no time and resources to recruit and train enumerators in the concepts utilized in this research.

3.4 Sampling

There is no uniform method of sampling in social research. The choice of the sampling method depends on the nature of the population, the resources available and the objectives of the study. However, in most of the research, techniques that give a known probability for all members of the population are preferred.

This study followed snowball sampling method. Snowball sampling is defined by Bailey (1994: 438) as “a non-probabilistic form of sampling in which persons initially chosen for the sample are used as informants to locate other persons having necessary characteristics making them eligible for the sample”. This sampling method was chosen because the population of coffee farmers in the study area was not well enumerated making it difficult to locate samples from other sampling methods. The method allows the researcher to come in contact with a small group of relevant people and to use them to establish contact with others (Bryman, 2008). Castillo (2009) adds that it is a very applicable method especially in studies where subjects are hard to locate.

20

A list of coffee farmers obtained from the government agricultural extension officers was used as a sampling frame from which a total of 30 coffee farmers were randomly selected and invited for the coffee agroforestry workshop. After the workshop, each of these became a contact person for the researcher. They were later followed-up to their households and interviewed using a household semi-structured survey questionnaire. After the survey interview, each of the coffee farmers was then asked to suggest 5 coffee farming households around him from which 2 households were randomly selected for interviews. This random selection was done in order to reduce non-random sampling and biasness towards the inclusions of individuals with interrelationships. In cases where the household head was absent, a wife or husband was interviewed after acknowledgement of thorough knowledge about the management of the coffee farm. In case none of them was available or willing to participate, the household would be dropped and another one picked. In total, 72 farming households (only coffee farmers) were interviewed. Mostly the household head was interviewed.

3.6 Data collection methods

3.6.1 Secondary and socio-economic data

De Zeeuw and Wilbers (2004) highlight the importance of secondary data in getting a general picture and examining possible contradictions with earlier thoughts of the researcher. Accordingly, both published and unpublished literature related to the study area and the topic where reviewed. Such literature was obtained from local governments and NGOs. It included information on such issues like demography, biophysical environment and socio-economic conditions. Additionally, the data collected from key informants were very useful in ascertaining the socio-economic situation in the study area.

3.6.2 Primary data collection

De Vaus (1996) points out that the process of obtaining qualitative data especially through opinions can be complex. Because of this complexity, a multidisciplinary approach is often required. In this study, primary data sources were basically coffee farmers and this data was gathered through a combination of tools (Figure 3.6.2). This diversity of tools enabled data to be triangulated in order to increase its validity and reliability.

A. Key informants interviews

These are interviews with specially selected individuals who have a long period of experience in a certain community or specialized knowledge or skills in a certain topic (de Zeeuw and Wilbers, 2004). Chambers (1992: 519) emphasizes the importance of key informant interviews in unearthing “invisible crucial social facts” and getting a better 21 understanding of complex situations. The objective of using key informants is to collect information and gain more understanding of issues in a short period of time. Such information is used to develop a checklist for further investigation and to supplement the data collected using other tools (Jackson and Ingles, 1998). However, care must be taken when selecting key informants to ensure that various categories of people in the society are represented. Jackson and Ingles (1998) add that researchers should take note that this tool should be supplemented with other tools in order to collect sufficiently reliable data.

Figure 3.6.2: Primary data collection process (source: prepared by the author)

According to Jackson and Ingles (1998), people like village elders, local leaders or school teachers, are very knowledgeable about issues and local needs and interests and they can be valuable sources of information. In this study, key individuals with outstanding experience and knowledge of the study area were identified during the reconnaissance survey and later interviewed. These were selected with the objective to ensure that all key stakeholders in coffee agroforestry within the study area are represented. A total of 6 key informants were interviewed in the study area. These interviews were primarily useful in the early stages of this study when the researcher was still trying to gain an overview of the study area.

In addition, formidable research institutions mandated to conduct agroforestry research were also visited and interviewed. These were considered to have a wide overview of the coffee

22 agroforestry discipline in the country. Overall, 4 specialists were interviewed and these data were used to supplement data collected with other tools.

B. Coffee farmers‟ workshop

Key considerations were made by the researcher prior to the use of the workshop for data collection and observations were made that: (1) there is a growing use of workshops in data collection (Franzel et al. 1996; Franzel et al. 2001; Souza et al. 2010) (2) this method was especially important where subjects are highly knowledgeable and validity of data requires challenging each other‟s views in the plenary (3) it was not in the interest of the researcher to investigate issues according to gender, age groups, wealth status, or any such categorization. Consequently, a farmers‟ method was preferred to the focus group discussions in this study.

A total of 30 Coffee farmers were randomly selected from a sampling frame which was provided by the government agricultural extension officers. These were then invited for a one day workshop in order to get their views and perceptions and tap their special knowledge regarding agroforestry tree species in Robusta coffee cultivation systems. All these farmers had special knowledge about coffee agroforestry which helped to gain deeper insights on issues of investigation.

The main objective of the workshop was to investigate the criteria used by coffee farmers to select tree species for intercropping with coffee. In this regard, a matrix of options and criteria (Horne and Stür, 2003) was used. A list of tree species which were agreed upon by the farmers to be the most common in coffee agroforestry in the study area was developed. These trees were appraised against the criteria for tree species selection and then ranked according to the farmers‟ preference. Farmers were also asked to define in their opinion the management levels of the coffee agroforestry systems. A scale3 which they believed could better evaluate the management levels of the coffee farms was developed. This scale was later used by the researcher during on-farm-observations.

C. Household survey A semi-structured questionnaire was used to collect data from the sampled coffee farm households. It is highly regarded for its flexibility to follow-up on questions depending on the response of the interviewee (de Vaus, 1996). Semi-structured interviews engaged the

3 A scale of 1-3 was used. 1 = Poor management: no defined spacing of coffee, no proper coffee tending practices e.g. pruning of coffee, limited shade for coffee, maximal tillage; 2 = Good management: intermediate between poor and very good; 3 = Very good management: clearly defined spacing of coffee, nice coffee tending practices, minimal tillage, enough shade for coffee. 23 respondents on issues related to the study using a list of prepared topics and questions to guide the discussion. This enabled a more elaborate investigation on key aspects related to the research (Bryman, 2008). The number of semi-structured interview conducted for this study was 72.

D. On-farm observations Sometimes, the information collected by other tools, such as semi-structured interviews, may not reflect the exact picture. This is because at times respondents can fail to verbalize issues during interviews. Worse still, they may misunderstand some questions. This tool provides an opportunity to triangulate the verbal information already collected and to gain a better picture of the situation on the ground (Jackson and Ingles, 1998; de Zeeuw and Wilbers, 2004). Jackson and Ingles (1998: 36) add that it can be used to make qualitative or quantitative appraisal of relevant physical and social conditions. This increases the reliability and accuracy of data collected. In order to ensure that data collected reflect the exact picture of the coffee farm, on-farm observations and informal discussions were used to compliment data collected with the other tools. Special emphasis was placed on the management levels in the different coffee cultivation systems; tree species, their arrangement and evidence of tree-crop interactions. During these observations, some tree species that had been forgotten during the interviews were sometimes identified and named by the farmer. However, these tended to be species of very few individuals, and were often disregarded. Where necessary photographs were recorded using a digital camera on the request of the farmer.

Tree species identification Soto-Pinto et al. (2007) argue that farmers have more knowledge about indigenous tree species. Their knowledge about exotic tree species is often limited especially in technical aspects. However, they are able to identify and differentiate between tree species grown on their farms with simple identification name tags. Sinclair and Walker (1999) found that farmers in Nepal for instance identified and differentiated tree species varieties despite some aggregation of agro-ecological knowledge. Similarly, farmers in Bukomansimbi were able to differentiate between tree varieties of indigenous and exotic species.

Consequently, it was not necessary to carry botanical samples of trees for identification. All the trees found growing in the study area had local names mentioned by the farmers. Even in the most complex situations involving trees of the same species, like it was the case with Albizia chinensis and Albizia coriaria where one is indigenous and another exotic, farmers still differentiated between the two with some nametags e.g. „Omugavu omuganda‟ (referring to A. coriaria) and „Omugavu omuzungu‟ (referring to A. chinensis). These local names were 24 later assigned scientific names using a compilation by Katende et al. (1995) and in consultation with list of scientific names and local names which was obtained from SCC-Vi Agroforestry project (see Appendix 2).

3.7 Data analysis and presentation

Data collected through the household survey was edited, coded and entered into the data input mask created using EPI Info software. Upon completion, the raw data was then exported to SPSS (Statistical Package for the Social Sciences) software. Both SPSS and Excel spreadsheets were used interchangeably during data analysis.

De Vaus (1996) notes that the complexity of research questions governs the method of data tabulation and analysis. Consequently, data analysis was done in accordance with the research questions and analyzed data were summarized in form of tables and graphs in order to facilitate easy understanding. Statistical data analysis involved the use of descriptive and inferential analytical techniques. Cross tabulation analyses using Chi-square tests (P < 0.05) to determine statistical independence between variables were carried out.

In order to generate socio-economic variables which discriminate between coffee agroforestry cultivation systems, a Discriminant analysis was used. The basis for selection of variables to run in the discriminant test was based on the principle that a case is excluded from the analysis if it contains missing information for the variable that defines groups or for any of the predictor variables. Interpretation of the analysis was based on standardized coefficients and the classification summary. The larger the standardized coefficient, the greater was the contribution of the respective variable to the discrimination between the coffee cultivation systems (Norusis, 1990). Using these predictor variables, a given cultivation system could be determined.

25

CHAPTER 4

PRESENTATION OF RESULTS

4.1 Social and farm characteristics of the coffee farmers A total of 72 farmers composed the household survey sample of which 51 were males and 21 females (Table 4.1). The average age of the sample was 49.6 (±1.3) with a range of 25- 80 years. Around 69.5% of the sampled farmers had attended primary school while around 22.2% and 6.9% attended secondary school and tertiary institutions respectively. Only 1.4% of the sampled farmers did not attain any level of formal education. More than two-thirds (88.9%) of the sampled farmers had land size between 1 ha and 5 ha (Table 4.1). Generally, all farmers had good experience of coffee farming with the majority (76.4%) having spent more than 10 years in coffee farming.

Table 4.1: Characteristics of coffee farmers interviewed during the household survey Variable Frequency [n] Percentage[%] Sex Male 51 70.8 Female 21 29.2 Formal education level None 1 1.4 Attended primary 50 69.5 Attended secondary 16 22.2 Attended tertiary 5 6.9 Farm size >1.0-≤2.0 14 19.5 >2.0-≤3.0 21 29.2 > 3.0-≤4.0 14 19.4 >4.0 -≤5.0 15 20.8 >5.0 8 11.1 Period growing coffee (years) 1 - 10 17 23.6 11 - 20 33 45.8 21 - 30 12 16.7 >31 10 13.9 Informal education in AF Yes 47 65.3 No 25 34.7 Need to grow more trees in coffee Yes 53 73.6 No 19 26.4 Hindrances to more growing Yes 43 70.5 No 10 29.5 Source: Field research (2011)

Around 65.3% of the sampled farmers had informal education in coffee agroforestry through NGOs (72.3%), government programmes (26.4%), media (22.2%), neighbors (20.8) and farmer organizations (10.6%) as the main sources. While 53 (73.6%) of the sampled farmers

26 still needed to grow more trees on their coffee farms, around 81.1% of these had hindrances in planting their desired tree species (see section 4.4 for the main hindrances).

Although the majority of the farmers relied on Robusta coffee (Coffea canephora) for household income, other crops were also being grown. Bananas (Musa paradisiaca), seasonal crops such as maize (Zea mays) and beans (Phaseolus vulgaris), vanilla (Vanilla planifolia) and vegetables such as such as tomatoes (Lycopersicon esculentum), cabbages (Brassica oleracea) and nakati (Solanum aethiopicum) were the other major types of crops in the study area. All these crops had also been mentioned by key informants.

Along the continuum of importance to the household, coffee was ranked first by the majority (73.6 %) of the sampled farmers among the 5 crop types. The rest (26.4 %) of the sampled farmers ranked it second after either banana or seasonal crops. Banana was ranked second overall by the interviewed farmers. From the key informant interviews, coffee, banana and seasonal crops were also regarded as the main sources of agricultural income in the area.

4.2 Classification of Coffee agroforestry cultivation systems

4.2.1 Classification criteria

Based on the main components of the coffee farm, coffee agroforestry cultivation systems were distinguished (Table 4.2.1). Only 3 farmers (4.2 %) out of the 72 interviewed did not fall in any of the three agroforestry cultivation systems because they had full sun coffee (monoculture) systems. These were left-out of the analysis of the coffee agroforestry cultivation systems since coffee monocultures could not be regarded among agroforestry practices. 69 farmers (95.8%) had coffee agroforestry cultivation systems.

Table 4.2.1: Main coffee agroforestry cultivation systems Code Main components Classification Other observations 1 Coffee, trees, Subsistence based - The vertical structure can be 3 or more stories seasonal crops cultivation system depending on the number of crops intercropped - Trees occupy the upper story followed by coffee and seasonal crops - Coffee was distributed in patches - Often poor management** 2 Coffee, banana, The Banana-coffee - 3 stories existed with trees occupying the first trees intercropping story, banana the second and coffee the third system story - Trees were mixed but sparsely arranged - Generally good management** 3 Coffee, trees Traditional shaded - 2 stories were distinguished with trees occupying cultivation system the top layer and densely spaced, while coffee occupied the lower layer - A closed layer of coffee under a mixed dense arrangement - Generally very good management** **Refer to section 3.6.2 for the management levels defined by the farmers. Source: Field research (2011) 27

Of the 69 farmers, 23.2% (16) had more than one coffee agroforestry cultivation systems on their farms. These were also later left-out in the Discriminant analysis as it could only be used for farmers with only one cultivation system. These were the 76.8% (53) of the sampled farmers of which around 37.7% (20) had Traditional shaded cultivation system, 39.6% (21) had Banana-coffee intercropping system and 22.6% (12) had the Subsistence based cultivation system.

4.2.2 The Subsistence based cultivation system

The system was termed „Subsistence based‟ owing to the fact the productivity of coffee as the cash crop was not the main objective of the farmer. In this system, trees were often sparsely distributed as they were considered to be direct competitors with seasonal crops (Plate 4.2.1). However, there was no special tree management rationale. Fruit trees were given priority for their productive functions perhaps to supplement household farm output. Coffee only received management priority after the harvesting of seasonal crops. A host of seasonal crops were found to be growing in this system. The seasonal crop combination differed from farmer to farmer. Some of the crops identified in this system include beans (Phaseolus vulgaris), maize (Zea mays), cassava (Manihot esculenta) and groundnuts (Arachis hypogaea). Even when a lot of management attention was given to seasonal crops, poor yields were often registered. Farmers attributed this to degraded soils and stiff competition between components.

a b Plate 4.2.1: Subsistence-based cultivation system. Coffee and sparse trees with; (a) cassava and sown beans (b) beans only. Field research (2011)

4.2.3 The Banana-coffee intercropping system

The system consisted of well managed components (Plate 4.2.2). Management priority was sometimes equally divided between coffee and banana. The grown tree species were often heavily pruned to minimize the negative effects on the intercrops (See Plate 1, Appendix 3). Only trees that were believed to have less negative effects to the crops were found to be 28 dominant on the farm. Such trees were selected for their protective functions such as soil conservation, moisture conservation, shade, etc. Farmers believed that banana and coffee were complementary to each other and that this led to better productivity of the coffee farm.

Some farmers mentioned that banana would be phased out (for a period of up to 3 years) when productivity reduced usually after 10 years, but also argued that this period could be extended with high management standards of the coffee farm. In instances of banana phase- out, new banana suckers could be replanted after about 3 years.

a b Plate 4.2.2: The banana coffee cultivation system; (a) and (b) showing good management for all components involved. Field research (2011)

4.2.4 The Traditional shaded cultivation system

This system was termed „traditional‟ as it mimicked the way coffee plants grow naturally as shrubs under dense forest canopies. Additionally, it is the oldest practice since the idea of intercropping coffee with other crops only evolved later. The vertical structure of the system was composed of two canopy layers, with trees occupying the top layer (Plate 4.2.3). Management ranged from intermediate to very high levels. There was a continuum of the degree of canopy closure from the much open canopy (especially during juvenile stages) to a dense canopy (at maturity). Trees of both protective and productive functions were found to be grown in this system.

29

a b Plate 4.2.3: The traditional coffee agroforestry cultivation system with Ficus natalensis; (a) light canopy and (b) dense canopy. Field research (2011)

4.2.5 Predicting a given cultivation system

In order to identify socio-economic variables that are important for distinguishing among the different coffee agroforestry cultivation systems, a Discriminant analysis was used. The analysis was applicable to 73.6% (53) of the sampled coffee farm households who had only one of the three coffee agroforestry cultivation systems. Results revealed that the variables which can best discriminate between the three cultivation systems are education level, informal education in agroforestry, main farm inputs and land size (Table 4.2.2).

Table 4.2.2: Relative importance of variables Variable Standardized coefficients Education level {1,2,3,4} 0.010 Fertilizer input {0,1} 0.407 Informal education {0,1} 0.529 Land size(ha) {1,2,3,4,5} 0.801 Formal education: 1 = none, 2 = Primary level, 3 = Secondary level, 4 = Tertiary level. Fertilizer input and Informal education: 0 = No, 1 = yes. Land size: 1 = >1.0-≤2.0, 2 = >1.0-≤2.0, 3 = > 3.0-≤4.0, 4 = >4.0 -≤5.0, 5 = >5.0. Empty cells indicate that there was no farmer. Source: Field research (2011)

The importance of each variable in predicting a classification was assessed based on the standardized coefficients (Table 4.2.2). The analysis gave positive standard coefficients indicating that an increase in any of the variables leads to a transition from a poorly managed Subsistence based cultivation system to a better managed Traditional shaded cultivation system. For example when land size increases from classes 1-5 the probability of getting the better managed Traditional shaded cultivation system (code 3, Table 4.2.1) increases. Land size, with the highest standardized coefficient of the four variables (Table 4.2.2), has the greatest impact on the final discriminant score. Thus land size discriminates more between the cultivation systems followed by informal education, fertilizer input and education level (Table 4.2.2).

30

The classification table (Table 4.2.3) depicts predicted frequencies of groups from the analysis as well as the actual frequency of groups found in the data. For example in the predicted group membership, of the 25 cases that were predicted to be in the Traditional shaded cultivation system, 15 were correctly predicted and 10 were incorrectly predicted (7 were predicted to be in the Banana-coffee intercropping system and 3 were predicted to be in the Subsistence based cultivation system). On the other hand, based on the frequencies of groups found in the data, it can be seen for example that of the 20 cases that were in the Traditional shaded cultivation system, 15 were predicted correctly and 5 were predicted incorrectly to be in the Subsistence based cultivation system. Generally, of the original grouped cases, 67.9% were correctly classified which is only close to two-thirds. Consequently, although they were the most important ones in this analysis, they cannot be relied upon in predicting a given system accurately.

Table 4.2.3: Classification table of the different agroforestry cultivation systems Cultivation System Predicted Group Membership 1. Subsistence 2. Banana-Coffee 3. Traditional based intercropping shaded Total Original Count: 1. Subsistence based 9 0 3 12 2. Banana-Coffee intercropping 2 12 7 21 3. Traditional shaded 5 0 15 20 %: 1. Subsistence based 75.0 0.0 25.0 100.0 2. Banana-Coffee intercropping 9.5 57.1 33.3 100.0 3. Traditional shaded 25.0 0.0 75.0 100.0 Cross-validateda Count: 1. Subsistence based 9 0 3 12 2. Banana-Coffee intercropping 4 10 7 21 3. Traditional shaded cultivation 5 0 15 20 %: 1. Subsistence based 75.0 0.0 25.0 100.0 2. Banana-Coffee intercropping 19.0 47.6 33.3 100.0 3. Traditional shaded 25.0 0.0 75.0 100.0 a. Cross validation is done only for those cases in the analysis. In cross validation, each case is classified by the functions derived from all cases other than that case. b. 67.9% of original grouped cases correctly classified. c. 64.2% of cross-validated grouped cases correctly classified. Source: Field research (2011)

An increase in a set of socio-economic variables shifts the cultivation system from a poorly managed Subsistence based cultivation system to a better managed Banana coffee intercropping and Traditional shaded cultivation systems (Table 4.2.4). Individually, some variables like informal education in agroforestry and fertilizer input tend to discriminate better between Subsistence based cultivation system and the two other systems combined. Land size appears to discriminate best between the three systems. However, in order to increase the accuracy of the prediction, a combination of all the four variables must be considered.

31

Table 4.2.4: Frequencies of farmers subscribing to a given variable in each cultivation system System Formal education Informal Fertilizer Land size education input 1* 2* 3* 4* Yes No Yes No 1** 2** 3** 4** 5** (1) (0) (1) (0) Subsistence-based 1 11 4 8 0 12 8 2 2 coffee agroforestry system Banana coffee 13 6 1 13 7 15 6 4 12 1 4 intercropping system Traditional coffee 10 9 1 18 2 16 4 1 3 10 5 1 agroforestry cultivation system *Formal education: 1 = None, 2 = Primary level, 3 = Secondary level, 4 = Tertiary level. **Land size: 1 = >1.0-≤2.0, 2 = >1.0- ≤2.0, 3 = > 3.0-≤4.0, 4 = >4.0 -≤5.0, 5 = >5.0. Empty cells indicate that there was no farmer. Source: Field research (2011)

4.2.6 Tree species distribution among cultivation systems Tree species composition across all systems included both indigenous and exotic tree species. Based on tree species frequencies, the subsistence based system was dominated by Artocarpus heterophyllus (83.3%), Mangifera indica (58.3%) and Persea americana (50%). In the Banana-coffee intercropping system, Ficus natalensis (95.2%) was mainly the most dominant. Ficus natalensis (65%), Maesopsis eminii (55%) and Artocarpus heterophyllus (45%) were the most dominant species in the Traditional shaded cultivation system. Tree management varied amongst the systems from low management in case of the Subsistence based cultivation systems to good and very good management in case of both the Traditional shaded cultivation system and Banana-coffee intercropping system.

4.3 Criteria for selecting coffee agroforestry tree species

Farmers listed several tree attributes and their respective indicators in the coffee farmers’ workshop which according to their experience were considered important for the coffee agroforestry system. The main criteria and indicators for selecting trees to use in coffee agroforestry systems were grouped into two; primary and secondary criteria (Figure 4.3.1). Primary criteria were considered by the farmers to be the most important and were ranked according to their importance. Secondary criteria could only be considered once the tree species had been evaluated against the primary criteria. In the primary criteria, the main criterion was optimal shading habits to coffee. Indicators of this were semi-deciduousness, small leaves, high branching and tree rotation (Figure 4.3.1). Semi-deciduous trees were preferred for this criterion because coffee requires light shade to ensure high flowering and attain very high yields. Small leaves are a signal to a light canopy since they allow some light to pass through to coffee plants. By high branching, farmers basically referred to the ability of the tree to produce branches at a reasonable height. High branching trees according to the farmers often produced spreading crowns there by

32 providing better shade for coffee. Trees of long rotation period were considered to provide shade long enough for the coffee plants.

Figure 4.3.1: Criteria (boxes) and indicators (ovals) used to select trees used in coffee agroforestry systems in Bukomansimbi district, Uganda. Source: Own elaboration (2011)

The second criterion was the ability of a tree to add nutrients to the soil. The main indicators for this were residual production, presence of root nodules and soft leaves (Figure 4.3.1). By residues, farmers referred to the quantity and quality of litter. For instance, farmers mentioned that some tree species, especially fruit trees, only released leaves which are yellow and take long to decompose. Yellow leaves do not contain enough nutrients to enrich the soil. Some trees, especially Albizia spp, were mentioned to posses root nodules which are an indicator of nitrogen fixation potential to the soil in addition to their nutrient rich litter. Accordingly, soft leaves indicated the ability of the litter to easily decompose and make nutrients available to the soil.

The third criterion among the primary criteria was production diversity. Farmers overwhelmingly noted that a tree which offered an opportunity to diversify the agroforestry system would be easily selected due to the diverse needs of a farm household. The indicator for this criterion was the ability of the tree to contribute products both for home consumption and the market. Such products included quality and quantity of food produced for humans and livestock as well as other products used in the day today life such as firewood and small building materials.

There was no prioritization among the secondary criteria. Whichever was used for selection depended on the needs of a particular farmer. The criteria listed were strong anchorage, less 33 labor intensiveness, attraction of pollinators, and non-hazardousness. One of the indicators for strong anchorage was presence of the light canopy to allow wind to filter through. In addition lack of a tap root system was believed to pose a threat to both humans and coffee as trees could easily be blown over during storms.

Indicators of less labor intensiveness were self-pruning and absence of superficial roots. Self-pruning trees were believed to require less management since they would pose no tree branches resting on coffee plants. Superficial roots according to farmers were an indicator of a strong competition with coffee plants for below ground resources such as water and mineral nutrients.

For attraction of pollinating insects especially bees, timely and heavy flowering was mentioned as a key indicator. Farmers argued that tree flowering should coincide with coffee flowering so that visiting insects can as well pollinate coffee plants. Tree species like Calliandra calothyrsus and Sesbania sesban were known by farmers to produce a lot of flowers which attracted pollinators especially bees.

35

30 32.4 30 25 20 19.3 15 18.3 10

Percentageoffarmers [%] 5 0 Optimal shading Production Nutrient addition Compatibility diversity Selection criteria

Figure 4.3.2: Most important selection criteria from the household survey. Source: Own elaboration (2011)

During the household interviews, farmers stressed the importance of certain tree attributes such as optimal shading habits, nutrient addition to the soil, production diversity and compatibility with coffee as being required for consideration in coffee agroforestry tree species selection (Figure 4.3.2). Of all farmers (69) who grow or retain tree species on their coffee farms, 32.4% mentioned that optimal shading is the most important consideration. 30% of the farmers refer to production diversity (i.e. ability of the tree to produce diverse products) as the main consideration. Around 19.3% of the farmers mentioned nutrients addition to the soil as a selection criterion. Around 18.3% of the farmers mentioned

34 compatibility with coffee which according to farmers meant that the tree species should offer minimal or no negative effects to coffee.

In the coffee farmers’ workshop, farmers generated a list of tree species which they considered to be the most grown with coffee in the area (Table 4.3). These species were evaluated according to the tree selection criteria (Figure 4.3.1). All participating farmers had very good knowledge about the species in question as they kept challenging each other‟s views. The results of the evaluation indicated that Albizia chinensis was regarded the most ideal tree species followed by Ficus natalensis and Albizia coriaria. Maesopsis eminii, Calliandra calothyrsus, Polysius fulva and Sesbania sesban were also rated highly.

Table 4.3: Matrix of options and criteria constructed with farmers Options (trees species) Criteria (tree attributes) Score Rank Optimal Production Strong Less labour Attracts Non- shading Nutrients diversity anchorage intensive pollinators hazardous x4 x3 x2 x1 x1 x1 x1 Albizia chinensis 88 69 40 23 21 16 22 271 1 Ficus natalensis 96 60 60 23 20 259 2 Albizia coriaria 88 45 32 25 4 8 20 222 3 Maesopsis eminii 112 44 22 16 4 198 4 Calliandra calothyrsus 75 36 15 20 2 148 5 Polysius fulva 92 10 22 13 2 139 6 Sesbania sesban 54 36 7 3 18 12 130 7 Persea americana 16 24 60 10 12 2 124 8 Artocarpus heterophyllus 24 60 17 7 8 116 9 Markemia lutea 21 34 20 13 8 96 10 Mangifera indica 60 10 5 3 78 11 Grevillea robusta 20 30 19 2 6 77 12 Faidherbia albida 12 27 9 5 17 70 13 Carica papaya 48 2 8 58 14 Numbers in the cells refer to the number of farmers out of 30 who voted for the tree species as fit for a given criteria; blank cells indicate that farmers did not vote for this tree species. All criteria are weighted with the primary criteria taking 2-4 in accordance with the scale of importance and the secondary criteria taking 1 (since there was no prioritization). Source: Field research (2011)

4.4 Major tree species grown on the coffee farms

The implementation at farm household level was rather different from the suitability ranking developed in the farmers‟ workshop. While the list of species which were found growing on the coffee farms did not vary so much from that generated from the workshop, the order of frequency of the tree species (Table 4.4.1) did not follow the suitability ranking (Table 4.3). Some species although highly evaluated by farmers in the workshop were not found to be integrated into coffee farms to a promising level. Such species include for example Calliandra calothyrsus, Sesbania sesban, and Polysius fulva. On the other hand, fruit trees

35 such as Artocarpus heterophyllus, Mangifera indica, Persea americana, which are not highly regarded for their suitability in coffee (Table 4.3), were found to be highly grown in practice.

Regarding the top five tree species (Table 4.4.1), the higher the frequency of farmers acknowledging products from a given species, the higher the total frequency of that tree species. A Chi-square test of independence between the grown tree species and products showed a very high dependence (P=0.000 for each of Ficus natalensis, Artocarpus heterophyllus, Maesopsis eminii, Mangifera indica, Persea americana and Albizia chinensis).

Table 4.4.1: Trees, their uses and main products according to their overall frequency Tree species Frequency Uses Main products [n] S F P A 1 2 3 4 5 6 7 Ficus natalensis 61 48 43 47 59 12 34 2 35 6 Artocarpus heterophyllus 37 7 37 5 37 5 Maesopsis eminii 29 16 28 11 28 Mangifera indica 22 2 21 22 21 Persea americana 22 4 21 22 22 Albizia chinensis 13 11 12 5 6 7 3 Sesbania sesban 9 9 7 4 9 9 Grevillea robusta 9 2 9 6 6 9 Albizia coriaria 9 7 5 3 4 5 1 Polysius fulva 8 8 7 8 Markhamia lutea 7 6 2 1 6 Carica papaya 2 2 2 2 Calliandra calothyrsus 2 2 2 1 Moringa spp. 2 1 2 Faidherbia albida 1 1 Psidium guajava 1 1 1 1 S = Shade, F = Fertility, P = Products, A= Attracts pollinators. 1 = Firewood, 2 = Fruits, 3 = Timber, 4 = Bark cloth, 5 = Medicine, 6 = Fodder, 7 = Poles. The numbers in the columns of uses and main products indicate the frequency of farmers acknowledging a particular use or main product. Source: Field research (2011)

Further analysis using Chi-square tests was carried out to find out whether informal education has an influence on the most grown tree species with coffee in the area (Table 4.4.2). For each of the tree species, there was generally no influence of informal education on its growing.

Table 4.4.2: Pearson’s Chi-square test p-values for tree species against informal education Tree species Ficus Maesopsis Albizia Mangifera Artocarpus Persea natalensis eminii chinensis indica heterophyllus americana Significance 0.13 0.972 0.106 0.156 0.94 0.156 No significant differences at P<0.05. Source: Field research (2011)

36

4.5 Uses and main products of trees grown

Almost all farmers acknowledged firewood as the most important tree product to the household. To this regard, Ficus natalensis was commended for its high biomass production as well as sprouting ability. Sprouting ability in particular was deemed essential by the farmers because of continuous need for fuel wood harvesting. Ficus natalensis offered all products apart from fruit production, some of which like bark cloth4 have high cultural values to the community. The tree represents a very strong cultural heritage among the Baganda tribe because of the bark cloth. This tree is also very much liked for its fodder and its ability to sprout gives it an edge over other species. While controlling the intensity of shade reaching the coffee plants, farmers could keep harvesting most of these products without having to kill the tree. Thus the tree is able to provide the same products for so many years without compromising its service functions.

From the household survey, 84.7% of the sampled farmers grow Ficus natalensis, followed by around 51.4% who grow Artocarpus heterophyllus and around 40.3% who grow Maesopsis eminii. Around 30.6% of the farmers grow either of Mangifera indica and Persea americana both of which are fruit tree species. Fruit tree species were much more considered compared to other species except for Ficus natalensis and Maesopsis eminii.

70 60 62.3 50

40 43.4 30 20 20.8

Percentageoffarmers [%] 10 15.1 13.2 0 Albizia Ficus Persea Mangifera Maesopsis chinensis natalensis americana indica eminii Tree species

Figure 4.5: Farmers’ desired tree species for enriching coffee fields. Source: Own elaboration (2011)

Farmers were asked whether they wanted to plant more trees in their coffee fields and which tree species they wanted to plant. The majority of the farmers (73.6%, Table 4.1) expressed interest in incorporating more agroforestry trees into their coffee plantations. Farmers were

4 Bark cloth (commonly referred to as Olubugo) symbolizes the Baganda tribe’s granary of creativity and resourcefulness. It has strong ritual importance and it is used as a cultural cloth in most of the cultural functions. 37 interested mainly in planting Albizia chinensis (62.3%), Ficus natalensis (43.4 %) Persea americana (20.8%), Mangifera indica (15.1%) and Maesopsis eminii (13.2%) (Figure 4.5). The superseding reasons given for more planting were products for both home consumption and sale (43.9%), addition of nutrients to the soil (33.7%) and ability of the tree to offer optimal shade to coffee (22.4%). Farmers associated optimal shade to having a light canopy which also indicates the tree‟s compatibility level to coffee. Specific trees mentioned for each use category were (1) nutrients to the soil: Albizia chinensis and Ficus natalensis (2) products: Ficus natalensis, Persea americana, Mangifera indica and Maesopsis eminii (3) optimal shade: Albizia chinensis and Ficus natalensis.

Unfortunately, approximately three quarters of the farmers interviewed (70.3%, Table 4.1) were unsuccessful in incorporating their preferred tree species into their coffee farms due to lack of planting materials (81.4%), small sizes of the farm (13.9%) and lack of technical knowledge about the desired tree species (4.7%). For instance the majority of farmers who mentioned Albizia chinensis highlighted lack of planting material as their prime hindrance.

4.6 Farmers’ perceptions on tree species grown

4.6.1 Positive effects of trees on coffee

A number of positive effects of agroforestry trees on coffee were mentioned by the farmers based on their day today observations on the coffee farm (Figure 4.6.1), the foremost one being microclimate amelioration (77.8%). In their opinion, coffee plants receive several physiological benefits from trees mainly associated with reduced plant stress. The easing of adverse climatic and site-specific stresses is accomplished through the reduction of air and soil temperature extremes in addition to reduced wind speed and suppressed weeds.

90 80 70 77.8

60 63.9 50 52.8 40 30 34.7 20 30.6

Percentageoffarmers [%] 10 18.1 0 Microclimate Nutrients to Erosion Physical Water Others the soil control protection conservation Positive effects

Figure 4.6.1: Positive effects of agroforestry trees on coffee. Source: Own elaboration (2011)

38

Nutrient addition to the soil was also mentioned by sampled farmers (63.9%) as another positive effect. In this regard, some trees such as Albizia chinensis and Albizia coriaria were highlighted as nitrogen fixers. Some of the trees especially Ficus natalensis and Albizia spp. were also known to shade green leaves which according to farmers are very rich in nutrients. These leaves were said to decompose instantaneously and help to add fertility to the soil.

Planting trees in coffee according to farmers (52.8%) helped to reduce soil erosion during heavy down pours. The tree canopies reduce the impact of the rain drops and enhance water infiltration. Yet at the same time tree roots were known to improve or maintain soil structure.

Farmers (34.7%) also mentioned that trees offered physical protection to coffee against stress factors such as wind, hailstorm and drought. According to the farmers, these stress factors caused damage to coffee especially during flowering.

In addition, farmers (30.6%) also mentioned water conservation as one of the positive effects of trees. According to farmers, tree canopies reduced direct sunshine to reach the ground in addition to their leaves which help to mulch the ground.

There were some other minor positive effects which were mentioned by the farmers (18.1%) such as: trees hosting natural enemies, attracting pollinators and improving the quality of coffee. Some natural enemies like birds were said to eat grasshoppers and caterpillar which feed on coffee and keep their populations below economic levels. Trees such as Sesbania sesban were known for their heavy flowering which attracted coffee pollinators especially bees. Farmers also mentioned that coffee grown under shade is has better quality than sun coffee.

4.6.2 Negative effects of trees on coffee

Farmers pointed-out some major drawbacks associated with agroforestry tree species in coffee that they had observed in their day to day management of coffee farms (Figure 4.6.2). Around 55.2% of the farmers mentioned resource competition as a major problem. Trees competed with coffee for below ground resources such as nutrients and water. Resource competition if it existed led to drastic reduction in coffee yield.

Around 21.1% of the sampled farmers mentioned that some of the tree species grown, posed a problem of over-shading to coffee plants thereby drastically reducing coffee yield if this shade was not managed. Moreover managing it meant extra labor demands to the already poor farmers. Among the tree species mentioned for this conundrum were almost all fruit trees, especially Artocarpus heterophyllus and Mangifera indica. For these tree species, farmers also complained about the inability of their leaves to decompose instantly (see Plate 39

2A, Appendix 2). Their leaves for example would prevent water infiltration during light rains. Additionally, the tree species themselves possessed superficial roots which competed with coffee directly for below ground resource.

Some trees were mentioned by the sampled farmers (26.3%) to be facilitating pests and diseases if not well-managed. Ficus natalensis was particularly mentioned for the fact that it facilitated the spread of CWD, a disease which had caused tremendous economic damage to coffee production in Uganda. It had been observed by some farmers that the impact of the disease on coffee plants was higher under Ficus natalensis than anywhere else on the coffee farm. Some farmers were individually removing this tree species from coffee. For instance in some fields, Ficus natalensis was being cut down while other farmers preferred to kill the trees by cutting off a ring of the bark (see Plate 3, Appendix 2). CWD was the prime disease for coffee with no eradication. Once the plant had been attached, it dried up and farmers could only continue replacing as they waited for resistant varieties which were expensive.

60

50 55.2

40

30

20 26.3 21.1

10 Percentageoffarmers [%] 5.6 0 Resource Facilitates pests Overshading Physical damage competition and diseases Negative effects

Figure 4.6.2: Farmers’ opinion on negative effects of trees on coffee. Source: Own elaboration (2011)

About 5.6% of the farmers had observed physical damage to coffee by some tree species. Species linked to this mystery were mainly Ficus natalensis, Maesopsis eminii (see Plate 4, Appendix 2). Ficus natalensis could be uprooted by strong wind as its roots did not strive deep down. Maesopsis eminii on the other hand had a firm tap root but its branches were reported to be very susceptible to storms. The harvesting of fruit from fruit trees also coincided with the coffee flowering and often led to damage during fruit fall and trampling of the ground by humans.

40

Table 4.6.2: Farmers’ observation of tree negative effects associated to the major tree species grown Tree species Frequency [n] Negative perception on major tree species

Ficus natalensis 25 Associated with CWD, host to dangerous insects, susceptible to wind Artocarpus heterophyllus 17 Poor leaf decomposition, competition for water and nutrients, Poor shade Maesopsis eminii 11 Competition for nutrients/water, susceptible to wind

Mangifera indica 6 Poor decomposition of leaves, poor shade Persea americana 4 Poor decomposition of leaves, susceptible to wind, poor shade

Grevillea robusta 4 Competition for nutrients/water Markhamia lutea 3 Competition for nutrients/water, susceptible to wind Source: Field research (2011)

Overall, Ficus natalensis received the highest number of complaints (25 farmers) about its negative effects to coffee, followed by Artocarpus heterophyllus (17 farmers) (Table 4.6.2). This is in contradiction with the expectation that farmers‟ perceptions of the negative effects of trees on the associated coffee would strongly influence their decisions to integrate such trees on their coffee farms. Apparently, Ficus natalensis and Artocarpus heterophyllus were the most grown tree species with coffee in the area (Table 4.4.1).

4.6.3 Tree species establishment and management

Farmers reorganized that the planting of trees often required time and financial resources in case planting materials were not readily available. They often exploited the cheapest possibilities much as they remained selective of the trees species they allowed in their coffee field. The means of establishment mentioned by the farmers for the tree species found growing on their coffee farms were vegetative regeneration, seedlings, direct sowing of seeds, and wildings (Table 4.6.3). Ficus natalensis was the only tree species being established by cuttings. The rest of the tree species were established using wildings and seedlings. Wildings were obtained from natural regeneration and they could sometimes be retained at the very site or transplanted to a preferred site on the coffee farm. Seedlings for most of the exotic non-fruit tree species were mainly obtained from NGOs (mainly SCC-Vi Agroforestry Project). Only a few farmers were able to purchase some of their preferred species. For some tree species that existed in the area for a long time such as fruit trees and some timber tree species like Maesopsis eminii, seedlings were often raised by the farmers from locally collected seeds. Direct sowing was often done for Calliandra calothyrsus and Sesbania sesban because of their fast juvenile growth. Some of the tree species which farmers pointed out to have been exclusively obtained from NGOs included; Sesbania sesban, Grevillea robusta, Calliandra calothyrsus, Moringa Spp.

41

Table 4.6.3: Species establishment and source of planting materials Establishment Tree species Source of planting material Seedlings Artocarpus heterophyllus , Albizia chinensis, Persea NGOs, purchased americana, Mangifera indica, Maesopsis eminii, Grevillea robusta, Polysius fulva, Carica papaya Psidium guajava, Moringa spp. Direct sowing Calliandra calothyrsus, Sesbania sesban NGOs, from own farm Wildings Artocarpus heterophyllus , Ficus natalensis, Persea Natural regeneration americana, Mangifera indica, Maesopsis eminii, Albizia coriaria, Markhamia lutea, Faidherbia albida cuttings Ficus natalensis Locally collected from own farm or neighbors Source: Field research (2011)

There was basically no rationale for locating agroforestry trees on coffee farms. In most of the cases, trees were found to be intercropped with coffee but with no particular spacing pattern. Despite strong claims that fruit trees presented stiff competition to coffee for resources (light, water, nutrients) they were commonly found to be intercropped with coffee.

In order to minimize negative consequences of trees on coffee, pruning (mainly for branches) was basically the only management practice performed on trees. Although it was superlatively known by the farmers that trees with dense canopies would be managed by pruning to reduce overshading to coffee, fruit trees were exempted because this, according to the farmers, meant a reduction in their fruit production. It is important to note that farmers‟ knowledge of tree origin sometimes differed so much from the existing literature. For example, most of the fruit trees were known by the farmers to be indigenous.

42

CHAPTER 5

DISCUSSION OF RESULTS

5.1 Classification of Coffee agroforestry cultivation systems

The study revealed three major coffee agroforestry cultivation systems namely: Subsistence based cultivation system, the Banana-coffee intercropping system, and the Traditional shaded cultivation system. The classification was based on the main components (vegetational complexity) of the coffee farm (cf. Moguel and Toledo, 1999) as well as quantity and quality of coffee per unit area. The three systems exhibited different management levels with the better management levels being observed in both Banana-coffee intercropping system and the Traditional shaded system. This was probably because of the rudimental means of production used by farmers in the Subsistence based cultivation system, the majority of whom had less than 2 hectares of land. Tree species composition included both indigenous and exotic tree species and there was generally no difference in the tree species used across all cultivation systems.

The Subsistence based system The Subsistence based cultivation system was integrated in ensuring that the subsistence needs of the household are met rather than the high productivity of coffee. The system was mainly practiced by smallholder famers and it was often characterized by low or no application of agrochemicals in the coffee field. Tree species were retained from wildings or planted deliberately. Fruit tree species (Artocarpus heterophyllus, Mangifera indica and Persea americana) were the most preferred in the Subsistence based cultivation system probably because of their contribution to the household food security and income demands (Somarriba, 1992; Snelder and Lasco, 2008). Sherr (1995) notes that farmers tend to adopt and adapt tree species which they consider relevant to their priority needs. This is true to this cultivation system where farmers widely acknowledged the use of fruit trees for food security as one of them pointed out:

“During periods of famine, we depend on Jackfruit (from Artocarpus heterophyllus) and Avocados (from Persea americana) for food”- Mr. Lutaaya Robert A host of crops being grown in the system comply with the livelihood strategy of the farmers in this system (Bacon, 2005; Rice, 2008). Poor yields for all components were reported mainly due to high soil degradation which was being caused by poor management of the coffee farm.

43

The Banana-coffee intercropping system

The Banana-coffee intercropping system although very popular in Uganda also occurs in other parts of the world. In Indonesia for example, it occurs with fruit trees such as Psidium guajava dominating the woody component (Godoy and Bennett, 1989). In Uganda, the system has a wide range of tree species and it‟s basically practiced by smallholder famers (Oduol and Aluma, 1990). It involves coffee as a cash crop and banana as a food crop with both crops contributing significantly to the farm income output (Oluka-Akileng et al., 2000; van Asten et al., 2011). Whereas the main goal of the system was the production of coffee, bananas were also highly regarded. The combination of banana and coffee in the system provided a means of diversification especially for smallholder families and led to a combined output from each of the components for marketing. It also offered a good balance between subsistence and market oriented production since bananas were also used to support the households for food. Farmers revealed that bananas helped to protect coffee against solar radiations in its juvenile stage when it was so sensitive to overheating and capable of drying out. In addition, farmers in Bukomansimbi also used Draceana fragrans (locally called Oluwanyi) to provide temporary shade during the early stages of coffee establishment.

A profitability study conducted on Banana-coffee intercropping (without trees) compared to the mono-cropped systems of Robusta coffee revealed a reduced total output of Robusta coffee in the intercrop but an increased total farm output (van Asten et al., 2011). This was because the reduction in coffee yield was compensated for by the output from bananas. Thus, it was concluded that Banana-coffee intercropping is much more viable than banana or coffee mono-cropping (van Asten et al., 2011). It could not be identified from the literature how long the Banana-coffee intercropping system can maintain its productivity. However, most farmers believed that the viability period of the system increased with improved management. Generally, it was mainly the bananas that were phased out in case their yield reduced significantly and Robusta coffee was left to grow for years.

Multipurpose trees were found to be intercropped in the system but mainly for service functions rather than products, and the density was considerably low compared to the traditional shaded system. Trees were specially selected and only multipurpose trees believed to have less negative effects to either component were found to be intercropped (Oduol and Aluma, 1990). Exotic tree species whose effects were still being keenly followed by the farmers and other tree species believed to have negative effects were found to be planted courteously sometimes at boundaries. This is supported by Oluka-Akileng et al. (2000) who found that scattered trees maintained in the Banana-coffee intercropping system were those perceived to compete minimally or not at all with the companion crops. Consequently in Bukomansimbi, Ficus natalensis which has a long tradition in the area, was 44 the most grown. Farmers believed that this tree species was complimentary to both coffee and banana.

Unlike the belief that most of the multipurpose trees on cropland mainly originate from natural regeneration (Oduol and Aluma, 1990), trees species in this system mainly originate from deliberate planting. However, they are heavily pruned to minimize over shade to intercrops.

The Traditional shaded cultivation system

In some countries, the Traditional shaded systems have been classified as being much complex with coffee being grown under forest remnants (Moguel and Toledo, 1999; Grossman, 2003; Souza et al., 2010, Aerts et al., 2011). In countries like Mexico, Brazil and Ethiopia, the traditional shaded system is born out of a simplified forest structure with just the removal of the forest understorey. This is perhaps attributed to the emergency of certified organic coffee production which restricts the use of agrochemicals (Grossman, 2003). In such a system, a reduction in shade has been found to increase coffee productivity (Aerts et al., 2011). Shade is however important in ensuring long-term productivity and improving coffee quality (Muschler, 2001; DaMatta, 2004; Vaast et al., 2006).

The Traditional shaded system in Bukomansimbi was managed with a reduced shade tree cover and density which involved retaining or planting preferred shade trees in coffee fields. Although the system mimicked in some cases the way coffee grows as a shrub in the forest, the diversity of tree species was incidentally low. This is probably because of the lack of organic coffee production commitment in Uganda which implies less dedication to the use of complex shade systems.

There was much more dominance of indigenous trees than their exotic counterparts. The most dominant tree species were Ficus natalensis (probably because of its multipurpose nature) and Maesopsis eminii (for timber). In their study, Teketay and Tegineh (1991) also discovered that Ficus spp. together with legumes were the most preferred species in the traditional tree crop based agroforestry in coffee producing areas of Harerge Ethiopia because of their multipurpose nature.

Addition of agrochemicals was more frequent compared to the other systems (Grossman, 2003). This is because with lack of organic coffee markets, farmers found it more rewarding to increase their coffee production through use of agrochemical. The main goal of the system was increased coffee yields. Thus the coffee farm output was directed exclusively to the market except for some tree products that were used both for subsistence and market.

45

5.2 Discriminating between coffee agroforestry cultivation systems

Figure 5.2 shows a supposed progression from the Subsistence based cultivation system to the Traditional shaded cultivation system. The x-axis represents farm management while the y-axis represents the discriminant variables in a given household. The diagonal line represents the supposed progression as a result of increase in discriminate variables.

If education level increased, there was a possibility that farmers became more innovative and open to better management strategies (Reed, 2007, Muneer, 2008) since formal education augments latent managerial capacity and a greater cognitive ability. Marenya and Barrett (2007:525) noted in their study that the managerial effect of secondary and tertiary education was uniformly larger than that of primary education. This is further supported by Blaug (1970)) and Murage et al. (2011. Rogers (2003) also contends that educated farmers usually have access to more information sources and can comprehend and benefit more from extension messages. Additionally, the higher the education levels, the higher the possibility of finding off-farm income which may be essential in accessing farm inputs such as agrochemicals and tree seedlings (Marenya and Barrett, 2007). This also helps farmers to increase their investment capital in assets like land. The result is better farm planning and farm management thus shifting from subsistence to market oriented production systems.

Figure 5.2: A hypothetical pathway to predict an agroforestry cultivation system in Bukomansimbi Uganda

The importance of informal education in the adoption of agroforestry technologies has been emphasized (e.g. Schuck et al., 2002; Muneer, 2008; Spielman et al., 2008). Informal education especially from NGOs has had a positive and significant effect on the possibility of 46 a well managed coffee cultivation systems in Bukomansimbi (see Figure 2.8) and likewise plays a big part in the hypothetical transition. If farmers are well informed about agroforestry, they will tend to use their resources and invest in a system which is better rewarding, implying better decision making ability (Kuntashula and Mafongoya, 2005). Depending on whether they are interested in diversification or increased coffee productivity, they will choose to transit a system which better fits in the kind of resources they have. Moreover informal education can supplement the deficit in farmers‟ formal education (Marenya and Barrett, 2007; Muneer, 2008). This is why contact with extension staff is likely to increase adoption of better technologies which may lead to better farm management (Rogers, 2003).

Land size was the most discriminating variable between the different cultivation systems. The increasing land size was perhaps proxy for other factors unaccounted for in the Discriminant analysis especially the possibility to grow other crops elsewhere on the household farm. Land is by far the biggest asset in most developing countries and one of the components of the natural capitals emphasized in the sustainable livelihood framework literature (e.g. Bebbington, 1999). It is regarded as a measure of wealth in most of the rural communities.

There is a conception that trees tend to compete with other crops for resources especially in small landholdings (Muneer, 2008). This notion is muted where land is large enough to enable the farmer to allocate different plots to different systems. Thus large household farms made the land available for traditional coffee systems since trees were not perceived at the expense of household food security (Muneer, 2008). In addition, given the fact that coffee is widely grown under tree shade, it is much probable that the increase in land size favored a transition to the Traditional shaded cultivation system since more land implied more room to plant trees (Biggelaaw and Gold, 1995). Although high tree abundance may not necessarily reflect high diversity, the density of tree cover cements the suggestion of agroforestry systems as antidotes to natural forest degradation (Blackman et al., 2008).

5.3 Criteria for selecting coffee agroforestry tree species

Developing a tree species selection criteria scheme by the farmers and allowing them to evaluate agroforestry tree species against these criteria presents an enormous opportunity to research and extension to promote tree species that will be efficiently adapted to the existing farming systems. As Scherr (1995) noted, trees selected have to meet a wide range of expectations from the farmer ranging from environmental to socio-economic needs of the farmers.

47

The set of criteria presented in this study (Figure 4.3.1) was generally agreed upon by all participants in the coffee farmers‟ workshop despite the fact that it could certainly lead to selection of different tree species at household level. Some criteria and indicators were similar to those found in Chipas, Mexico (Soto-Pinto et al., 2007) and Atlantic Rain biome (Souza et al., 2010). While the study in Chipas highlighted the different indicators of suitability and unsuitability of shade species for coffee (Soto-Pinto et al., 2007), it fell short of the proper criteria on which indicators were based. The study by Souza et al. (2010) was much more elaborate and defined criteria and their indicators. Some of these criteria such as labor intensity and production diversity are similar to those found in this study. In addition, farmers in Bukomansimbi elaborated a whole range of other criteria (Figure 4.3.1).

Unlike in Zona da Mata (Souza et al., 2010), the primary criteria for selecting tree species was optimal shading. Suitable species for this criterion had to be semi-deciduous because light is needed during coffee flowering to ensure high coffee yield (Soto-Pinto et al., 2000). The semi-deciduousness also renders pruning unnecessary thereby saving labor and time (Souza et al., 2010). In addition, trees with small leaves were preferred as they were perceived to offer better shade compared to their counterparts. A typical example given by the farmers was Albizia spp. Beer (1987) supports this by noting that small leaves minimize rain drop coalescence and subsequent drip damage. Unlike in some studies (Albertin and Nair, 2004; Soto-Pinto et al., 2007), farmers in Bukomansimbi preferred high branching tree species. They argued that a tall tree although may not be easy to manage, its branches could not rest on coffee plants and was capable of producing a spreading crown for optimal shade in coffee (Beer, 1987). Farmers in Bukomansimbi also preferred long-term tree species for optimal shading in coffee fields. This is supported by Beer (1987) who notes that optimal shade can only be guaranteed if the tree lives long enough to outlast the coffee plants.

The second most regarded criterion was the ability of a tree to add nutrients to the soil. Readily decomposing pruned materials and litter are regarded as major sources of soil fertility (Beer, 1987; Kuntashula and Mafongoya, 2005; Souza et al., 2010). Farmers mentioned that tree species, especially fruits which shade yellow leaves, did not add nutrients to the soil since such leaves took long to decompose. Green leaves according to the farmers were richer in nitrogen than yellow leaves. Li et al. (2011) support this when they note that high quality litter has a low C/N ratio and will decompose rapidly and make nutrients available. Presence of root nodules was a major indicator of a tree‟s ability to add nutrients to the soil. Root nodules contain nitrogen fixing bacteria which fix atmospheric nitrogen into the soil. Beer (1987) supports the idea that shade trees in coffee should be nitrogen fixing. Additionally, the use of nitrogen fixing trees may reduce the cost of fertilizers (Souza et al., 48

2010). However, some studies reveal that the added nitrogen is generally low on its own to justify the inclusion of legumes (Fassbender, 1987). Nevertheless, the impact of the fixed nitrogen depends on the site conditions (Szott et al., 1991; Neupane and Thapa, 2001).

The diversification of production was mentioned by farmers as an important criterion and probably justifies their use of native and/or fruit trees. It is argued that farmers often adopt agroforestry technologies which give better benefits (Scherr, 1995). Trees contribute to food security and a higher benefit/cost ratio of the coffee agroforestry system. As Beer (1987) found out valuable tree products are well regarded in shaded coffee systems. In some cases, income from such products has been reported to be significant (Soto-Pinto et al., 2007; Snelder and Lasco, 2008).

If the tree met the primary criteria, secondary criteria would then be considered, namely; strong anchorage, less labor intensiveness, attraction of pollinators and non-hazardousness (Figure 4.3.1). Unlike the primary criteria, secondary criteria were not ranked by the farmers according to importance. The main indicators of strong anchorage were a light canopy and a taproot system. These enabled the tree not to be susceptible to wind throw (Beer, 1987). A light canopy was particularly important in that it allowed air circulation minimizing the chances for a tree to be thrown.

Self pruning trees with no superficial roots were considered important for minimizing labor costs. Specifically for timber, self pruning trees are capable of straight bole formation and knot free timber (Beer, 1987). Trees with superficial roots often competed with coffee for below ground resources such as water and nutrients. Beer (1987) adds that trees with deep roots attract nutrients from deeper layers which are not accessed by coffee.

Heavy flowering trees with scented flowers were known to attract pollinating insects like honey bees (Apis mellifera) especially if their flowering coincided with that of coffee. This is supported by a study in Mexico (Vergara and Badano, 2009) which revealed that the more structurally and floristically complex coffee management systems were, the higher was the species richness of insect pollinator communities as well as coffee fruit production.

Besides causing damage to coffee plants, hazardous trees were believed be dangerous to human beings during the management of the coffee fields. Thorny stems and branches could hinder management. At the same time, some tree species host insects and pathogens which damage coffee (Beer, 1987).

In the household survey, the importance of production diversity, optimal shading and nutrient addition was stressed by the farmers. Farmers highly value the importance of

49 diversification of production. It contributed to food security (in case of fruits) and increased the benefit/cost ratio of the coffee agroforestry system (Souza et al., 2010). It‟s probable that farmers had household specific priorities and therefore their tree planting in coffee farms was incorporated in the overall household livelihood strategy. Ellis (1993) argues that the high levels of uncertainties in farming forces farmers to exhibit high levels of risk aversion in their decision making. Likewise farmers in Bukomansimbi had to secure their household needs from their current production through diversification and prioritization of production. For instance, poor farmers may have planted quick yielding fruit trees than timber because the waiting time for timber trees was too long.

5.4 Major tree species grown on the coffee farms

The diversity of tree species in Bukomansimbi (16 species) was low compared to other studies conducted in areas of more traditional coffee cultivation. Rice (1999) found 24 tree species being used as shade in Southern Uplands of Nicaragua; Albertin and Nair (2004) mentioned 127 species found in Nicoya Peninsula, Costa Rica; Souza et al. (2010) listed 85 tree species found growing with coffee in the Atlantic Rainforest Biome, Brazil. In Bukomansimbi, the low species diversity is probably due to the relatively homogeneity in ecological and edaphic conditions.

Some species, although highly evaluated by farmers, based on the suitability ranking developed in the workshop, were not found to be practically integrated into coffee farms to a promising level. This is supported by Souza et al. (2010) who argue that even with similar selection criteria, the choice of species may still be different. Tree species selection always becomes frenetic when it is considered among the household objectives under risks and uncertainties. Some of the tree species which were rated highly in the workshop but did not feature well on the ground included Calliandra calothyrsus, Sesbania sesban, and Polysius fulva. On the other hand, fruit trees such as Artocarpus heterophyllus, Mangifera indica, Persea americana, which were not highly regarded for their suitability in coffee, were found to be highly grown in practice. This was a clear indication that the selection criteria proposed by the farmers may be adapted to fit their prevailing situations. It also signified that farmers do not make rational decisions as opposed to what is purported by Raintree (1983). The high level of risks and uncertainties coupled by the household demands, compel the farmer to concur with the theory of bounded rationality (Simon, 1972; Sonkkila, 2002).

The five most grown tree species by the farmers in Bukomansimbi were Ficus natalensis, Artocarpus heterophyllus, Maesopsis eminii, Mangifera indica, and Persea americana. Table 5.4 summarizes their ecology and uses in Uganda. These tree species were valued more for their productive functions (products) rather than service functions (shade and fertility). For 50 example around 86% of the product types harvested from coffee agroforestry systems in the study area could be harvested from Ficus natalensis in addition to its service functions (see Table 4.4.1). This multipurpose nature makes Ficus natalensis a priority tree species for coffee agroforestry in Bukomansimbi, bearing in mind that trees in agroforestry are much more valued for their multipurpose nature (Nair, 1993; Oluka-Akileng, et al. 2000; Neupane and Thapa, 2001).

Table 5.4: Summary of the species ecology and uses in Uganda Tree species Ecology Uses Remarks Ficus natalensis Indigenous to Uganda, the species is Medicine, shade, live Culturally important among cultivated in all regions of the fence, bark cloth, the Baganda tribe. country. firewood, timber and Often intercropped with It is a fast growing tree species with fodder. coffee and banana for shade coppicing ability. and nutrients. Propagated by large and small cuttings and also seedlings. Artocarpus Originates from India and was Food (fruit, seed), Suitable around compounds as heterophyllus introduced to Uganda in 1940s. firewood, charcoal, a shade tree. Propagated through direct sowing at high quality timber, Commonly intercropped with site and wildings. fodder, medicine, and coffee and banana in Uganda. shade. Direct sowing at site preferable due The fruit provides food to early growth of taproot. security especially during The tree fruits at different times periods of food shortage. depending on the age of the tree. Maesopsis eminii Indigenous to Uganda and it grows in Timber, firewood, One of the quickest growing low moist tropical forests, colonizing charcoal, poles, fodder timber trees maturing in 20 forest, forest edge and mixed forest. (fruits), shade. years. Propagated by seedlings, wildings, Can be intercropped with direct sowing at site. banana, coffee and cocoa Fast growing and coppices while mainly for shade. young. Mangifera indica Originates from India but widely Fruits, firewood, bee Mango trees should be pruned grown throughout Uganda. forage, shade, but in practice, pruning is Propagated through seedlings and windbreaks and limited to removal of dead grafting. medicine. branches. Direct sowing is possible. Persea americana Originates from tropical America but Food, cosmetics, Very nutritious fruit rich in fat, grown in all moist areas of Uganda. shade, firewood proteins and vitamins. Propagated by grafted materials The dense surface root system (improved varieties), seedlings and competes with those of crops. direct sowing. It’s a good money earner. Source: Adapted from Katende, et al. (1995) and Howard and Nabanoga (2007)

While informal education has been applauded for its influence on the adoption of agroforestry technologies (Schuck et al., 2002; Muneer, 2008; Spielman et al., 2008), analysis revealed that it had no influence on the most grown tree species. Grossman (2003) argues that farmers often posses knowledge gaps regarding phenomena despite training attempts. Besides, coffee agroforestry is a highly specialized field in such a way that extension workers

51 could fail to influence farmers‟ decision or it may be that extension efforts were focusing mainly on food crop production.

Albizia chinensis, an exotic tree species which is highly regarded by the farmers and widely promoted for coffee agroforestry by NGOs, was not being grown as expected. When farmers were probed about Albizia chinensis, lack of planting materials was the major drawback for its growing. Thus the promotion of such exotic tree species needs to be accompanied with a guarantee of planting materials. As the interviews with key informants revealed, farmers are more comfortable to adopt indigenous tree species because planting materials are readily available. The implication seems to be that development initiatives should not only provide technological options but also attempt to make up for the low levels of support materials.

One of the reasons for maintaining trees on-farm is the provision of products such as food, firewood, timber and medicine for household economies (Arnold, 1995). Coffee agroforestry systems contain a diversity of tree species to provide products of multiple uses. During risks and uncertainties, like they are in farming, it‟s rare that farmers select tree species based on one function. A study on fodder tree species in Kenya by Roothaert and Franzel (2001) discovered that all the native tree species used by farmers for fodder had other uses such as firewood, timber and medicine.

The use of traditional shaded systems for firewood is well documented especially in Mexico (Peeters et al., 2003). Conditions in Uganda attest to the fact that firewood is by far the most important source of energy especially in rural areas as it is the case elsewhere in developing countries (cf. Kuntashula and Mafongoya, 2005; Rice, 2008). The most important tree species for firewood mentioned by the farmers was Ficus natalensis. This is because of its fast growth rate, ability to sprout and long-term nature when compared to other species like Sesbania sesban. Its use for fire wood was also acknowledged in Tabuti et al. (2003) and Godfrey et al., (2010). The sprouting ability was essential for continuous supply of fuel wood. Agroforestry trees have to be continuously managed for services and products needed by the household. Beer (1987) mentions ability to resprout after being pruned as a key consideration during tree selection for coffee agroforestry. In addition to fuel wood, Ficus natalensis outstandingly offers fodder. This species has been reported in other parts of Uganda for its provision of fodder (Tabuti, 2009). Its fast sprouting ability gives it yet another edge over other species. Traditionally, Ficus natalensis is used for production of bark cloth which has high cultural values to the community (see Groth and Kamwesiga, 2002; Howard and Nabanoga, 2007).

52

Farmers in Bukomansimbi also prefer a variety of fruit trees such as Artocarpus heterophyllus, Mangifera indica, Persea americana. Since these trees were not evaluated highly for their service functions, it can be argued that their integration in the coffee agroforestry systems was based on products especially fruits which could support the poor farmers and help diversify their farm output. This is supported by investigating on the use of fruit shade trees in Guatemala and Peru by Rice (2011) in which he noted that fruits from coffee agroforestry systems can play an advanced role in use and exchange value especially during times of low coffee prices. This seems to be an entrenched feature of rural smallholder survival strategy.

Farmers in Bukomansimbi preferred certain tree species for their enrichment planting. Albizia chinensis and Ficus natalensis were preferred for optimal shade and additional nutrients to the soil, fruit trees such as Persea americana for fruit products for sale and Maesopsis eminii for timber. Since all the mentioned non-fruit tree species offered products such as timber and firewood, it would not be a surprise that products for home and sale was given as a superseding reason for more tree growing in the coffee agroforestry systems.

5.5 Farmers’ perceptions on agroforestry tree species grown

5.5.1 Positive perceptions

Farmers‟ awareness of the positive effects offered by tree species was evident throughout all the discussions. Farmers are inept of advanced scientific concepts but able to describe the observable improvements in health of coffee plants growing under some shade trees. For example mineralization is an abstract process that farmers observed indirectly based on the change in coffee plants‟ health and yields in comparison to unshaded or poorly shaded coffee plants. Albizia spp. (A. chinensis and A. coriaria) and Ficus natalensis were applauded by farmers for their ability to add nutrients to the soil through great amounts of decomposing litter. Some studies have revealed that some tree species are known to produce enormous amount of litter. For instance, Beer et al. (1989) found that the annual nutrient return via litter fall of Erythrina poeppigiana represented 90-100% of the nutrient store in its aboveground biomass.

Farmers were able to recognize the influence of microclimate amelioration on reduction of coffee stress. They observed for example that during dry spells, coffee plants located under shade never required a lot of care while those in open spaces would sometimes wilt-off. The importance of microclimate amelioration has been stressed elsewhere (e.g. Nair, 1993; Beer et al., 1998). In their review on shade management in coffee and cacao plantations, Beer et al. (1998) observed that amelioration of climate takes place in many ways one of which is the reduction of air and soil temperature extremes. 53

Farmers also mentioned addition of nutrients to the soil as another positive effect of trees in coffee fields. In this sense, Albizia spp. were noted by farmers for fertilizer addition to the soil. Farmers did not specifically mention nitrogen fixation although these are leguminous species capable of nitrogen fixation. In a study in Chiapas, Mexico, Grossman (2003) found out that farmers had excellent knowledge of the transformation of plant residues to soil and minerals. Likewise farmers in Bukomansimbi had observed the presence of root nodules on the roots of Albizia spp. Although they lacked full knowledge of the whole biological transformation process of nitrogen, they believed their presence led to the addition of nutrients to the soil. Fixation of nitrogen from the air and mineralization of nutrients from organic matter are some of the ways in which nutrients are made available to plants as noted by Szott et al. (1991). Additionally, the much popular use of Inga spp. in Mexico shaded systems is as a result of its ability to fix nitrogen and provide optimal shade (Peeters et al., 2003). Nitrogen fixation to the soil is also supported by a study by Young (1989) in which he reports that the return of nutrients from litter and pruning can be as high as 100-300 kg N ha- 1yr-1 in coffee and cocoa plantations with shade trees. Farmers in Bukomansimbi also mention the ability of some tree leaves to decompose very fast and add nutrients to the soil. They believed that leaves from Albizia spp. decomposed faster than leaves from fruit trees. This is supported by Nair (1993) who notes that the rate of leaf decomposition varies widely among tree species. Additionally, Li et al. (2010) note that some leaves have a low C/N ratio which helps them to decompose very fast and add nutrients to the soil. Moreover the potential of agroforestry trees to enhance fertility through decomposition of litter is very important especially in poor sites as it has been acknowledged in the middle hills of Nepal (Neupane and Thapa, 2001).

Planting trees in coffee according to farmers helps to reduce soil erosion during heavy down pours. Trees reduce the impact of rain drops on the ground and allow water to infiltrate into the soil. Trees increase soil cover and enhance soil organic matter which stabilizes the soil against erosion (Nair, 1993). According to Young (1990) and Nair (1993), the soil litter cover is much more effective against erosion than the tree canopy. The tree canopy helps to provide a supply of these materials through direct litter fall or pruning (Young, 1990:39).

Physical protection against wind and hailstorm especially during flowering and yielding was mentioned by farmers as an important function of agroforestry trees. This is supported by Nair (1993) who argues that trees as windbreaks can help to protect crops from loss of flowers.

54

5.5.2 Negative effects

Resource completion was cited as a major drawback between trees and coffee crops especially if trees are not well selected and managed. Much as trees are known to access soil volume beyond reach of the crop, some level of competition for below ground resources such as nutrients and water exits (Nair, 1993). Moreover this competition is more significant in poor sites and during unfavorable periods. Resource competition if it existed led to drastic reduction in the benefits which farmers would get in associating trees with crops. Whereas it has been argued that the root system of coffee is sufficiently competitive to restrict the rooting space of trees (Schaller et al., 2003), this may only be applicable where nutrients are high enough to match the requirements of both species.

Farmers also mentioned the problem of overshading. While shading causes a reduction of temperature fluctuations and helps create a favourable microclimate (Nair, 1993), coffee farmers in Bukomansimbi reported that overshading causes a reduction in coffee yield. Their observation is supported by DaMatta (2004) who found that coffee yields better under light shade. Some tree species, especially fruit trees such as Artocarpus heterophyllus and Mangifera indica were reported by farmers to produce dense shade. However, it is worth noting that overshading can help to suppress light demanding weeds (Szott et al., 1991; Nair, 1993).

There were also specific negative perceptions against some of the most grown tree species. Farmers‟ on-farm observation of negative effects mostly embraced tree species such as: Ficus natalensis, Fruit trees (Artocarpus heterophyllus, Mangifera indica, Persea americana), Maesopsis eminii, Grevillea robusta, and Markhamia lutea.

Despite the fact that it was the most widely grown tree species, Ficus natalensis was being linked to the spread of the deadly CWD believed to host some dangerous insects and also susceptible to wind throw. A combination of these had prompted some of the farmers to kill or discontinue its growing in coffee fields. Yet despite the growing wave of suspicion amongst the farmers linking Ficus natalensis to CWD, no scientific evidence has been identified in this regard. However, Huxley and Greenland (1989) argue that bacterial and fungal diseases may increase in shaded more humid environments. Some views among the interviewed farmers seemed to conquer with this argument:

“The high spread of the CWD under Ficus natalensis is due to failure by some farmers to manage their shade. When the shade is too much, the very high moist environment under Ficus natalensis favors the disease and this can happen under any shade, not only Ficus natalensis. Farmers should learn to prune their trees to control the moist conditions”- noted Mr. Kintu Frank.

55

Other farmers believed that these were baseless rumors and had different opinions:

“The wilt only happens when the Ficus natalensis tree is removed. As a result of a long-term relationship with the coffee trees underneath and the interaction between the roots of these plants, an abrupt shock is created to the coffee plants which in turn end up wilting”- argued Mr. Kagolo Jackson. His argument seemed to be in agreement with some of the farmers who believed that before the final harvesting of the Ficus natalensis, a replacement should be planted fast to provide some shade. The removal should also not be abrupt to avoid shock to the coffee plants.

“I cut a ring around the Ficus natalensis tree to allow it die gradually in one to two seasons and avoid shocking the coffee trees. This enables the remaining coffee trees to cope up with the new environment gradually rather than abruptly”- said Mr. Nteza Kkangave. However, in practice it was still hard for farmers to practice this gradual killing of Ficus natalensis. This method could only work if the final product was firewood. In cases where farmers were interested in timber or charcoal, an abrupt removal could not be avoided.

Timber trees like Maesopsis eminii, Markhamia lutea, Grevillea robusta were noted to be competing highly with coffee for resources especially nutrients and water. It was argued that these species consume a lot of water and do not add nutrients to the soil. Nevertheless, they were preferred for their products rather than service functions. Even in areas like Central America where coffee shade was being managed principally for the benefit of coffee, some diversification was reported in favor of timber species in response to insecure coffee prices (Schaller et al., 2003). Maesopsis eminii is believed to be the fastest growing timber species in coffee agroforestry with locally available planting material. The competition for water and nutrients is not the only revelation against timber tree species. Elsewhere, their inability to add nutrients to the soil had meant that most of the modified shaded systems focus so much on legumes which exclusively benefit the coffee plants (Schaller et al., 2003; Peeters et al., 2003).

Farmers also expressed their complaints against fruit trees (Artocarpus heterophyllus, Mangifera indica, Persea americana) for poor leaf decomposition and poor shade quality. While Szott et al. (1991) argue that slowly decomposing litter is known to suppress weeds more effectively than that which decomposes more rapidly, farmers in Bukomansimbi valued soil fertility more than weed suppression. Yet despite these complaints, fruit trees were found to be intercropped with coffee because of their ability to offer products for home consumption and sale.

56

5.6 Tree species establishment and management

The degree of the effects of trees on associated crops depends among other factors on the arrangement, planting density and management of trees (Nair, 1993). Most of the mentioned species by farmers were established through seedlings and wildings (Table 4.6). Despite several drawbacks related to wildings such as non-optimal densities and low genetic variability (Beer et al., 1997), farmers in Bukomansimbi relied so much on them. This perhaps explains the low stocking densities observed on some of the coffee farms. Another reason could be that farmers were concerned about the compatibility of certain tree species with coffee and they needed to plant them cautiously. It could also be that they probably lacked clear guidance of the stocking densities. Farmers may also have perceived reduced densities as being better for coffee yield. Some interviews supported this argument:

“Much as our organization promotes tree species such as Albizia chinensis, Ficus spp., Calliandra calothyrsus and Albizia coriaria; we have no profound information on their suitable stocking densities”- said Mr. Evan of Hanns R. Neumann Stiftung. Research organizations interviewed also attested to the fact that no research has been conducted to find-out the optimal densities of trees in coffee agroforestry in Uganda. The spacing adopted by some was based on experience rather than scientific rationale. Thus it is to no surprise that the decisions on where to locate the trees on the coffee farms were based on the validation which often differed among farmers.

Farmers had problems to access planting materials for many of the exotic tree species as compared to indigenous. Fruit trees (Artocarpus heterophyllus, Mangifera indica, and Persea americana were considered by most of the sampled farmers to be indigenous much as according to Katende et al. (1995) they are regarded exotic to Uganda. Seeds from such naturalized exotics5 could easily be collected from the communities and raised because the tree species provide extra income, food security and other outputs.

5.7 The farmers’ ideotype tree specification for coffee agroforestry

The evaluation in the previous sections has revealed that farmers were knowledgeable about the trees grown in coffee fields. The criteria and indicators put forward by the farmers were very important since it is the farmers who implement at the farm. In order to ensure adoptability of new technologies, scientists working in the area of agroforestry research must take note of these criteria. The methodologies and approaches suggested earlier, such as the D&D (Raintree, 1989) and the Multipurpose tree selection approach (von Carlowitz,

5 Naturalized exotics are tree species that have been grown by farmers for so long and their planting materials can easily be accessed from local settings. 57

1989) may not be quite applicable in very specific situations. It is the role of research to find models that can be applicable to a particular purpose.

Thus, based on the research findings in Bukomansimbi, an ideotype tree specification for coffee agroforestry scheme is elaborated (Figure 5.6). This specification can be of much relevance in promotion of coffee agroforestry research and extension in the study area based on the conceptual framework (Figure 2.8). However, it should be noted that it‟s very difficult to approximate an ideal tree for coffee agroforestry. As Nair (1993) notes, the selection criteria may differ depending on location and objectives.

Figure 5.6: An ideotype tree specification for coffee agroforestry in Bukomansimbi (Source: Prepared by the author)

Thus in the absence of a clear and specific tree selection model, the responsibility to select trees to be grown lies with the farmer. The decision is based on productive and ecological functions as well as social considerations. Several criteria are then considered based on these three pillars. The productive functions demand an ideal tree to produce marketable products and/or domestic products which are very important to support livelihood. The ecological functions refer to both site productivity and soil fertility. Social considerations imply that the tree should be accepted by the farming household and should not be a liability to the household.

58

CHAPTER 6

REFLECTIONS, CONCLUSIONS AND RECOMMENDATIONS 6.1 Reflections

6.1.1 Relationship between theory and findings

The knowledge gap hypothesis is derived from socio-economic variables. The strength of this theory is particularly rooted in the fact that it‟s supported by the diffusion of innovations theory (Rogers, 2003). The commonly used socio-economic variables in agroforestry literature were analyzed using a Discriminant analysis and a set of variables that could potentially be used to predict a given cultivation system was derived. The empirical results presented and discussed in the previous two chapters show that socio-economic variables such as formal education, fertilizer input, informal education and land size all influence the type of the coffee agroforestry cultivation system practiced by the farmer though at varying degrees.

The testable proposition was set to test the relevance of this theory in the current study, that is; “whether the implementation of a better managed coffee cultivation system is positively related to the improvement in a defined set of socio-economic variables” can be tested. Based on this proposition, the empirical results have demonstrated that the implementation of a better managed coffee cultivation system was positively related to the increase in formal education level, fertilizer application, access to informal education and above all increase in land size. Consequently, using these variables, one could roughly predict a given coffee agroforestry cultivation system.

6.1.2 Reflections on research questions

The first research question pertains to a set of variables which can be used to predict a coffee agroforestry cultivation system. The empirical results show that socio-economic variables such as formal education, informal education, fertilizer input and land size will determine the type of the coffee agroforestry cultivation system at varying degrees in the study area. These variables could be used to predict a given coffee agroforestry cultivation system.

Question two deals with the main tree species grown with coffee and reasons to why they are selected for coffee agroforestry. Results have revealed that the five most grown tree species were: Ficus natalensis, Artocarpus heterophyllus, Maesopsis eminii, Mangifera indica, and Persea americana. These tree species were valued more for their productive functions rather than service functions.

59

The third research question pertains to the tree attributes and their respective indicators considered by the farmers for suitability in coffee fields. The criteria and indicators considered important to coffee agroforestry were numerous and were all exhaustive from the point of view of the farmers. Criteria such as optimal shading habits, nutrient addition to the soil and production diversity, were of primary importance to the farmers‟ decision making while strong anchorage, less labor intensiveness, attraction of pollinators, and non- hazardousness were of secondary importance.

The last research question dealt with limitations of the main tree species found growing on the coffee farms. Farmers‟ on-farm observation of negative effects embraced all the five most grown tree species namely; Ficus natalensis, Artocarpus heterophyllus, Mangifera indica, Persea americana and Maesopsis eminii. The negative effects included affiliation to CWD (Ficus natalensis), resource competition, poor shade quality, lack of leaf decomposition (Artocarpus heterophyllus, Mangifera indica, Persea americana and Maesopsis eminii).

6.2 General conclusions

The study identified three coffee agroforestry cultivation systems, namely: Subsistence based cultivation systems, Banana-coffee intercropping system and Traditional shaded system. These systems were less diverse and less complex than those found in other studies (Moguel and Toledo, 1999; Grossman, 2003; Souza et al., 2010, Aerts et al., 2011). In all these systems, there was a reasonable dependency on trees grown for products and services. However, much of the dependency on products occurred in the Subsistence based system given the fact that fruit trees were the main trees grown.

Farmers were very knowledgeable about coffee agroforestry as depicted by the tree species selection criteria and the quality of discussions attained. The criteria and indicators that farmers considered important for coffee agroforestry trees species selection were comparable to those found in other literature. However despite these well elaborated criteria and indicators, the selection of a particular tree species was judged individually on the farm and this resulted in different tree species at the farm household level.

Many of the most common tree species such as Artocarpus heterophyllus, Mangifera indica and Persea americana were not considered of much benefit to coffee plants. Yet they were still maintained in coffee agroforestry systems because of their products to the household. Albizia chinensis and Ficus natalensis were considered the best species for coffee plants.

The number of development organizations promoting agroforestry through informal trainings in the study area must have had influence on the coffee cultivation systems practiced (see Chapter 4, section 4.2.5). However, the results revealed that informal education in 60 agroforestry had no influence on tree species planted in coffee agroforestry systems in the study area. Thus there is need for enforcement of farmer participatory evaluation of agroforestry tree species to integrate their knowledge and experiences as illustrated in the conceptual framework (Figure 2.8). In addition, the lack of planting materials for species such as Albizia chinensis which was much desired by the farmers signals inadequacies in the support materials given to farmers in the study area.

The reality remains that, it is very difficult to have an ideal tree species. In fact as seen in practice, farmers‟ decisions can be influenced by other factors which are quite urgent and important in their livelihood even when they know the most ideal option. The ideal tree model conceived in this study is specific to Bukomansimbi and should only be taken as a guide on a wider scale. Consequently, it is prudent to cautiously adapt this model to specific local conditions of similar ecological conditions and farming systems.

6.3 Limitations of the study

In full accordance with the research objectives, the current investigation focused on the evaluation of agroforestry tree species in Robusta coffee cultivation systems from the point of view of the farmers. There was lack of on-farm coffee agroforestry research trials in the area which if present would have provided a good opportunity for comparison. Nevertheless, this study paves way for future research based on participatory methods between farmers and research institutions.

In addition, no attempts were made in the current study to investigate the yield variations under different cultivation systems as well as agroforestry tree species. Although highly desirable, such investigations exceeded the material time and resources available to the researcher. Additionally, there is often a low level of farmers‟ comprehension of numerical questions related to income and expenditure, which made it quite difficult to integrate such work in the current study. Nevertheless, omission of such factors presents a limitation of the current study.

Agroforestry is a very complex discipline and it deals with an interplay of elements in both ecological and socio-economic nature and so is the farmer who may not necessarily focus on the coffee farm in isolation of other enterprises. By concentrating on the coffee farm, the study lost out on other enterprises whose management may be affecting decisions taken on the coffee farm. There was need to integrate coffee agroforestry system into the broad picture of the household.

61

6.4 Recommendations

This study has unveiled a list of priority species for coffee agroforestry in Bukomansimbi. Due to the very high interest of farmers in the study area, research needs to be conducted on species such as Ficus natalensis, Artocarpus heterophyllus, Mangifera indica, Maesopsis eminii and Persea americana which are the most common. Such studies should also unveil optimal stocking rates for each of the species.

Farmers‟ perceptions revealed interesting findings about the most grown tree species. There is no doubt that Ficus natalensis was by far the most preferred tree species in coffee agroforestry in Bukomansimbi. Yet it was being linked to the most devastating coffee disease in Uganda. Consequently, special research attention needs to be given to Ficus natalensis in relation to the farmers‟ claims that it facilitates the spread of CWD.

Development organizations working in the field of coffee agroforestry must integrate farmers‟ needs and preferences in their approach (Figure 2.8). While promoting tree species in coffee agroforestry systems, care must be taken to ensure that those being promoted meet a wide level of acceptance. One way would be to ensure that extension agents carryout needs assessments before planning interventions.

Most of the tree species being promoted in Uganda are not carefully tested and may not fulfill the expectations of the farmers. There is need to establish strong ties with farmers as implementers. One way to bridge this gap is to ensure that tree species being promoted, though not yet scientifically proven meet the acceptability criteria of the farmers. At the same time, there should be serious commitment by researchers to generate scientific information on these species in a way that involves the farmers as well (Figure 2.8). One of the options is the intensification of on-farm research where their experiences and knowledge can be integrated.

There is a need for reliable socio-economic studies about the most grown tree species to ensure wider broadening of opportunities for coffee farmers in the study area. Value addition and product chains from some of the tree species are areas which need to be thoroughly investigated and developed.

Research and extension programmes in Bukomansimbi where the majority of the coffee farmers had less than 4 hectares, must take into account that new technologies prove remunerative even to small scale farmers. Additionally, it is recommended that extension agents in the area address other socio-economic issues as well. Special care must be taken to ensure that farmers with poor socio-economic characteristics especially those practicing

62 the Subsistence based cultivation system are able to benefit from new technologies. Lobbying strategies for education and trainings as well as subsidized inputs can be another way of improving socio-economic characteristics of the farmers and preparing them for adoption of better rewarding technologies.

63

CHAPTER 7

LIST OF REFERENCES

Aerts, R., Hundera, K., Berecha, G., Gijbels, P., Baeten, M., van Mechelen, M., Hermy, M., Muys, B., Honnay, O. (2011). Semi-forest coffee cultivation and the conservation of Ethiopian Afromontane rainforest fragments. Forest Ecology and Management 261: 1034- 1041.

Albertin, A., Nair, P.K.R. (2004). Farmers‟ perspectives on the role of shade trees in coffee production systems: An assessment from the Nicoya Peninsula, Costa Rica. Human Ecology 34 (4): 443-463.

Amoah, F.M., Osei-Bonsu, K., Oppong, F.K. (1997). Response of improved Robusta coffee to location and management practices in Ghana. Experimental Agriculture 33: 103-111.

Arnold, J.E.M. 1995. Framing the issues. In: Arnold, J.E.M., Dewees, P.A. (eds). Tree management in farmer strategies: Responses to agricultural intensification, Oxford University Press, Oxford, 1-18.

Bacon, C. (2005). Confronting the coffee crisis: Can fair trade, organic, and specialty coffees reduce small-scale farmer vulnerability in northern Nicaragua? World Development 33(3): 497-511.

Bailey, K.D. (1994). Methods of social research. New York, Free Press

Bebbington, A. (1999). Capitals and Capabilities: A Framework for Analyzing Peasant Viability, Rural Livelihoods and Poverty. World Development 27(12): 2021-2044.

Beer, J. (1987). Advantages, disadvantages and desirable characteristics of shade trees for coffee, cacao and tea. Agroforestry Systems 5: 3-13.

Beer, J. (1989). Litter production and nutrient cycling in coffee (Coffea arabica) or cacao (Theobroma cacao) plantations with shade trees. Agroforestry Systems 7: 103-114.

Beer, J., Muschler, R., Kass, D., Somarriba, E. (1998). Shade management in coffee and cacao plantations. Agroforestry Systems 38: 139-164.

Biggelaaw, C.D., Gold, M.A. (1995). The use and value of multiple methods to capture the diversity of endogenous agroforestry knowledge: an example from Rwanda. Agroforestry Systems 30: 263-275.

Blackman, A., Albers, J.H., Avalos-Sartorio, B., Murphy, C.L. (2008). Land cover in a managed forest ecosystem: Mexican shade coffee. American Journal of Agricultural Economics 90(1): 216–231.

Blaug, M. (1970). An introduction to the Economics of Education. Penguin, London.

Bryman, A. (2008). Social Research Methods. 3rd Edition. Oxford University Press, Oxford.

Castillo, J.J. (2009). Snowball Sampling. http://www.experimentresources.com/snowball- sampling.html. Accessed 08th March, 2011.

64

Chambers, R. (1992). Rural Appraisal: Rapid, Relaxed and Participatory (Discussion Paper no.311). ISBN: 0-90371584-8. Institute of Development Studies, Sussex University, Brighton.

Compton, J.L. (1984). Linking scientist and farmer: Rethinking extension‟s role. In: Drosdoff, M., Ithica, N.Y. (eds). World food issues. Cornell University, International Agriculture Program 79-84.

DaMatta, F.M. (2004). Ecophysiological constraints on the production of shaded and unshaded coffee: a review. Field Crops Research 86: 99-114.

De Vaus, D.A. (1996). Surveys in social research. 4th edition. UCL Press, London.

De Zeeuw, H., Wilbers, J. (2004). PRA tools for studying urban agriculture and gender. Resource Center on Urban Agriculture and Forestry, Leusden. Online available: http://www.ruaf.org/sites/default/files/gender_tools.pdf. Date of access: 8.12.2010.

Ellis, F. (1993). Peasant economics: Farm households and agrarian develop development. Cambridge University Press. Cambridge, pp. 309.

Evenson, R.E. (1997). The economic contribution of agricultural extension to agriculture and rural development. In Swanson, B.E., Bentz, R.P., Sofranko, A.J.(eds). Improving agricultural extension: A reference manual. FAO, Rome Italy 27-36.

FAO (2009). State of the world‟s forests. Food and Agriculture Organization. Rome, Italy.

Fassbender, H.W. (1987). Nutrient cycling in agroforestry systems of coffee (Coffea arabica) with shade trees in the central experiment of CATIE. In: Beer, J.A., Fassbender, H.W., Heuveldop, J. (eds). Advances in Agroforestry Research. CATIE, Serie Tecnica 117: 155-165.

Franzel, S., Coe, R., Cooper, P., Place, F., Scherr, S.J. (2001). Assessing the adoption potential of agroforestry practices in the sub-Saharan Africa. Agricultural Systems 69: 37-62.

Franzel, S.; Jaenicke, H., Janssen, W. (1996). Choosing the right trees: Setting priorities for multipurpose tree improvement. International Service for National Agricultural Research, Hague.

Fresco, L.O., Huizing, H.G.J., van Keulen, H., Luning, H.A., Schipper, R.A. (1994). Land evaluation and farming systems analysis for land use planning. FAO Working Document. FAO, Rome.

Freudenthal, S., Narrow, J. (1991). Community baseline studies: Towards understanding context and concerns in community forestry. Development Studies Unit (DSU). Report No.19. Uppsala

Godfrey, A.J., Denis, K., Daniel, W., Akais, O.C. (2010). Household Firewood Consumption and its Dynamics in Kalisizo Sub-County, Central Uganda. Ethnobotanical Leaflets 14: 841-855.

Godoy, R., Bennett, C. (1989). Diversification among coffee smallholders in the highlands of South Sumatra, Indonesia. Human Ecology 16(4): 397-420.

Government of Uganda (2002). The National Forest Plan. Uganda forests. Republic of Uganda, Kampala. 65

Government of Uganda (2010). The background to the budget 2010/2011 fiscal year: Strategic priorities to accelerate growth, employment and socio-economic transformation for prosperity. Ministry of Finance, Planning and Economic Development, Kampala.

Grossman, J.M. (2003). Exploring farmer knowledge of soil processes in organic coffee systems of Chiapas, Mexico. Geoderma 111: 267-287.

Groth, G.N., Kamwesiga, J. (2002). Splinting materials old and new: Origins and application of bark cloth in upper extremity splinting. Journal of Hand Therapy 15(2): 202-204.

Hayami, Y., Ruttan, V. (1985). Agricultural Development: An International Perspective. Johns Hopkins Press, Baltimore, USA

Horne, P., Stür, W.W. (2003). Developing agricultural solutions with smallholder farmers: How to get started with participatory approaches. Australian Centre for International Agricultural Research (ACIAR), Canberra. Online available: http://www.ciat.cgiar.org/work/Asia/Documents/pdf/aciar_monograph99_contents.pdf. Date of access: 2/1/2011

Howard, P. L., Nabanoga, G. (2007). Are there customary rights to plants? An inquiry among the Baganda (Uganda), with special attention to gender. World Development 35(9), 1542-1563.

Huxley, P. (1999). Tropical Agroforestry. Blackwell Science, London.

Huxley, P.A. and Greenland, D.J. (1989). Pest Management in Agroforestry Systems. In: Huxley, P.A. and Greenland, D.J. (eds). A record of discussions held at CAB International, 28-29 July 1988. Agroforestry Abstracts 2: 37-46.

Jackson, W.J., Ingles, A.W. (1998). Participatory techniques for community forestry: A field Manual. IUCN, Gland, Switzerland and Cambridge, UK and World Wide Fund For Nature, Gland, Switzerland, xii + 124 pp. ISBN 2-8317-0384-0.

Katende, A.B., Birne, A, Tengnäs, B. (1995). Useful trees and Shrubs for Uganda: Identification, Propagation, and management for Agricultural and Pastoral communities. Technical Handbook No. 10. Regional Soil Conservation Unit. Nairobi, Kenya.

Klein, A.M., Steffan-Dewenter, I., Tscharntke, T. (2003). Bee pollination and fruit set of Coffea arabica and Coffea canephora (rubiaceae). American Journal of Botany 90(1): 153-157.

Kuntashula, E., Mafongoya, P.L. (2005). Farmer evaluation of agroforestry trees in eastern Zambia. Agricultural Systems 84: 39-53.

Li, L., Zeng, D., Yu, Z., Fan, Z., Yang, D., Liu, Y. (2011). Impact of litter quality and soil nutrient availability on leaf decomposition rate in a semi-arid grassland of northeast china. Journal of Arid Environments, 75(9): 787-792.

López-Gómez, A. M., Williams-Linera, G., Manson, R. H. (2008). Tree species diversity and vegetation structure in shade coffee farms in Veracruz, Mexico. Agriculture, Ecosystems & Environment 124(3-4): 160-172.

66

Lyngbaek, A.E., Muschler, R.G., Sinclair, F.L. (2001). Productivity and profitability of multistrata versus conventional coffee farms in Costa Rica. Agroforestry Systems 53: 205- 213.

Marenya, P.P., Barrett, C.B. (2007). Household-level determinants of adoption of improved natural resources management practices among smallholder farmers in western Kenya. Food policy 32: 515-536.

McGregor, M.J., Rola-Rubzen, M.F., Murry-Prior, R. (2001). Micro and Macro-level approaches to modeling decision making. Agricultural Systems 69: 63-83.

Moguel, P., Toledo, V.M. (1999). Biodiversity conservation in traditional coffee systems of Mexico. Conservation Biology 13 (1): 11-21

Muleta, D., Assefa, F., Nemomissa, S., Granhall, U. (2007). Composition of coffee shade tree species and density of indigenous arbuscular mycorrhizal fungi (AMF) spores in Bonga natural coffee forest, southwestern Ethiopia. Forest Ecology & Management 241: 145-154.

Muneer, S.E.T. (2008). Factors affecting Adoption of Agroforestry Farming system as a Mean of Sustainable Agriculture Development and Environment Conservation in Arid Areas of Nothern Kordofan State, Sudan. Saudi Journal of Biological Sciences 15(1): 137- 147.

Murage, A.W., Obare, G., Chianu, J., Amudavi, G.M., Pickett, J., Khan, Z.R. (2011). Duration analysis of technology adoption effects of dissemination pathways: A case of “push-pull” technology for control of Striga weeds and stem borers in Western Kenya. Crop Protection 30: 531-538.

Muschler, R. (1997). Shade or sun for ecologically sustainable coffee production: A summary of environmental key factors. In: Actas de la III. Semana Científica del Centro Agronómico Tropical de Investigación y Enseñanza (CATIE). CATIE, Turrialba, 109– 112.

Muschler, R.G. (2001). Shade improves coffee quality in a sub-optimal coffee-zone of Costa Rica. Agroforestry Systems 51: 131–139.

Muschler, R.G., Bonnemann, A. (1997). Potentials and limitations of agroforestry for changing land-use in the tropics: experiences from Central America. Forest Ecology and Management 91: 61-73.

Nair, P.K.R. (1993). An introduction to agroforestry. Kluwer Academic Publishers in cooperation with International Centre for Research in Agroforestry. Dordrecht, Netherlands.

Nestel, D. (1995). Coffee in Mexico: international market, agricultural landscape and ecology. Ecological Economics 15: 165-178.

Neupane, R. P., Thapa, G. B. (2001). Impact of agroforestry intervention on soil fertility and farm income under the subsistence farming system of the middle hills, Nepal. Agriculture, Ecosystems & Environment, 84(2): 157-167.

Neupane, R.P., Sharma, K.R., Thapa, G.B. (2002). Adoption of agroforestry in the hills of Nepal: A logistic regression analysis. Agricultural Systems 72: 177-196. 67

Norusis, M.J. (1990). SPSS/PC+ Advanced Statistics 4.0 for IBM PC/XT/AT and PS/2. SPSS inc.

Oduol, P. A., Aluma, J.R.W. (1990). The banana (Musa spp.) – coffee Robusta: traditional agroforestry system of Uganda. Agroforestry Systems 11: 213-226.

Oluka-Akileng, I., Esegu, J.F., Kandia, A.A., Lwakuba, A. (2000). Agroforestry Handbook for the Banana-Coffee zone of Uganda: Farmers‟ practices and experiences. Technical handbook No. 21. The Regional Land Management Unit, Sida. Nairobi, Kenya.

Peeters, L.Y.K., Soto-Pinto, L., Perales, H., Montoya, G., Ishiki, M. (2003). Coffee production, timber, and firewood in traditional and inga-shaded plantations in southern Mexico. Agriculture, Ecosystems & Environment, 95(2-3): 481-493.

Purseglove, J.W. (1968). Tropical crops: dicotyledons. Wiley, New York.

Raintree, J.B. (1983). Strategies for enhancing the adoptability of agroforestry innovations. Agroforestry systems 1: 173-187.

Raintree, J.B. (1989). The Diagnosis and Design Methodology. In: Huxley, P.A. & Westley, S.B. (eds). Multipurppose Trees: selection and testing for agroforestry, pp. 11-17. International Council for Research in Agroforestry, Nairobi Kenya.

Reed, M.S. (2007). Participatory technology development for agroforestry extension: an innovation-decision approach. African Journal of Agricultural Research 2(8): 334-341.

Rehm, S., Espig, G. (1991). The cultivated plants of the tropics and subtropics: cultivation, Economic value, utilization. Institute of Agronomy in the Tropics, University of Göttingen.

Rice, R. (1999). A place unbecoming: The coffee farm of northern Latin America. The Geographical Review 89: 554–579.

Rice, R. A. (2008). Agricultural intensification within agroforestry: The case of coffee and wood products. Agriculture, Ecosystems & Environment 128(4): 212-218.

Rice, R.A. (2011). Fruits from shade trees in coffee: how important are they? Agroforestry Systems, DOI 10.1007/s10457-011-9385-4

Rogers, E. M. (2003). Diffusion of innovations. 5th edition, The Free Press. New York

Romero-Alvarado, Y., Soto-Pinto, L., Garcia-Barrios, L., Barrera-Gaytan, J.F. (2002). Coffee yields and soil nutrients under the shades of Inga sp. versus multiple species in Chiapas, Mexico. Agroforestry Systems 54: 215-224.

Roothaert, R. L., Franzel, S. (2001). Farmers' preferences and use of local fodder trees and shrubs in Kenya. Agroforestry Systems 52: 239-252.

Schaller, M., Schroth, G., Beer, J., Jiménez, F. (2003). Species and site characteristics that permit the association of fast-growing trees with crops: The case of eucalyptus deglupta as coffee shade in Costa Rica. Forest Ecology and Management 175(1-3): 205-215.

Scherr, S.J. (1995). Economic Factors in Farmer Adoption of Agroforestry: Patterns observed in Western Kenya. World Development 23(5):787-804. 68

Schuck, E. C., Nganje, W., Yantio, D. (2002). The role of land tenure and extension education in the adoption of slash and burn agriculture. Ecological Economics 43(1): 61- 70.

Senkondo, E. (2000). Risk attitude and risk perception in agroforestry decisions: The case of Babati, Tanzania. Ph.D Thesis. Wageningen Agricultural University, Wageningen.

Simon, H.A. (1991). Bounded rationality and organizational learning. American Economic Review 49(3): 253-283.

Sinclair, F.L., Laxman, J. (2000). Taking local knowledge about trees seriously. In: Lawrence, A. (ed.) Forestry, forest users and research: new ways of learning. European Tropical Forest Research Network (ETFRN) series 1. Wageningen University, Netherlands 47-65.

Sinclair, F.L., Walker, D.H. (1998). A utilitarian approach to incorporation of local knowledge in agroforestry research and extension. In: Buck, L.E., Lassoie, J.P., Fernandes, E.C.M. (eds). Agroforestry in sustainable agricultural systems. CRC Press, Boca Raton 245- 275.

Snelder, D.J., Lasco, R.D. (2008). Smallholder tree growing in South and Southeast Asia. In: Snelder, D.J., Lasco, R.D. (eds). Smallholder tree growing for rural development and environmental Services. Springer 3-36.

Somarriba, E. (1992). Timber harvest, damage to crop plants and yield reduction in two Costa Rican coffee plantations with Cordia alliodora shade trees. Agroforestry Systems 18: 69–82

Sonkkila, S. (2002). Farmers‟ decision-making on adjustment into EU. Department of Economics and Management. University of Helsinki, Helsinki.

Soto-Pinto, L., Perfecto, I., Castillo-Hernandez, J., Caballero-Nieto, J. (2000). Shade effect on coffee production at the northern tzeltal zone of the state of Chiapas, Mexico. Agriculture, Ecosystems & Environment, 80(1-2), 61-69.

Soto-Pinto, L., Villalvazo-Lopez, V., Jimenez-Ferrer, G., Ramirez-Marcial, N., Montoyz, G. Sinclair, F.L. (2007). The role of local knowledge in determining shade composition of multistrata coffee systems in Chiapas, Mexico. Biodiversity and Conservation 16: 419- 436.

Souza, H.N., Cardoso, I.M., Fernandes, J.M., Garcia, F.C.P., Bonfim, V.R., Santos, A.C., Carvalho, A.F., Mendonca, E.S. (2010). Selection of native trees for intercropping with coffee in the Atlantic rainforest biome. Agroforestry Systems 80: 1-16.

Spielman, D. J., Ekboir, J., Davis, K., Ochieng, C.M.O. (2008). An innovation systems perspective on strengthening agricultural education and training in sub-Saharan Africa. Agricultural Systems 98(1): 1-9.

Szott, L. T., Fernandes, E.C.M., Sanchez, P.A. (1991). Soil-plant interactions in agroforestry systems. Forest Ecology and Management, 45(1-4): 127-152.

Tabuti, J. R. S., Dhillion, S. S., Lye, K. A. (2003). Firewood use in Bulamogi County, Uganda: Species selection, harvesting and consumption patterns. Biomass and Bioenergy 25(6): 581-596.

69

Tabuti, J.R.S. (2009). Fodder plants for cattle in Kaliro district, Uganda. African Study Monographs 30(3) : 161-170.

Tekentay D., Tegineh, A. (1991). Traditionla tree crop based agroforestry in coffee producing areas of Harerge, Eastern Ethiopia. Agroforestry Systems 16: 257-267.

Tichenor, P.J., Donohue, G.A., Olien, C.N. (1970). Mass media flow and differential growth in knowledge. Public Opinion Quarterly 34(2): 159-170.

UBOS (2007). Projections of Demographic trends in Uganda 2007-2011, volume 1. Uganda Bureau of Statistics, Kampala Uganda.

UCDA (2009). Annual report, volume 18. Ministry of Agriculture, Animal Industry and Fisheries, Kampala Uganda.

UCDA (2010). Overview/General. Online available: http://www.ugandacoffee.org/index.php?Itemid=49&id=36&option=com_content&task=vi ew. Date of access: 15/10/2010.

Vaast, P., Bertrand, B., Perriot, J.J., Guyot, B., Genard, M. (2006). Fruit thinning and shade improve bean characteristics and beverage quality of coffee (Coffea Arabica L.) under optimal conditions. Journal of Science Food Agriculture 86: 197–204.

Van Asten, P.J.A., Wairegi, L.W.I., Mukasa, D., Uringi, N.O. (2011). Agronomic and economic benefits of coffee–banana intercropping in Uganda‟s smallholder farming systems. Agricultural Systems, 104(4), 326-334.

Van Oijen, M., Dauzat, J., Harmand, J., Lawson, G. Vaast, P. (2010). Coffee agroforestry systems in Central America: II. Development of a simple process-based model and preliminary results. Agroforestry System 80: 361-378.

Vergara, C.H., Badano, E.I. (2009). Pollinator diversity increases fruit production in Mexican coffee plantations: The importance of rustic management systems. Agriculture, Ecosystems and Environment, 129(1-3): 117-123.

Von Carlowitz, P.G. (1989). Matching Trees with Technologies using ICRAF‟S MPTS DATABASE. In: Huxley, P.A., Westley, S.B. (eds). Multipurppose Trees: selection and testing for agroforestry, pp. 31-35. International Council for Research in Agroforestry, Nairobi Kenya.

Young, A. (1989). Agroforestry for Soil Conservation. CAB International, Wallingford, UK.

Young, A. (1990). Agroforestry for soil conservation. Science and Practice of Agroforestry, No. 4. ICRAF, Nairobi.

Links http://www.worldatlas.com/webimage/countrys/africa/ug.htm

70

LIST OF APPENDICES

Appendix 1: Questionnaires

A: Household semi-structured survey questionnaire

Date: Questionnaire ID: District: Sub-county: Parish: Village: Characteristics of the interviewed farmer 1. Age …………………

2. Sex 1. Male 2. Female

3. Formal education level: 1. None 3. Attended primary 2. Attended secondary 4. Attended tertiary

4. How long is the distance to the nearest trading center?

5. What is the form of land acquisition? (more than one possible): 1. Inherited 3. Purchased 2. Leased 4. Government allocation

6. What is the size of your farm? 1. > 0 - ≤ 1.0 4. > 3.0 - ≤ 4.0 2. > 1.0 - ≤ 2.0 5. > 4.0 - ≤ 5.0 3. > 2.0 - ≤ 3.0 6. > 5.0

7. What are the major agricultural enterprises on your farm? Agricultural enterprises Rank (according to importance to the hh) 1. Coffee 2. Banana 3. Vanilla 4. Seasonal crops 5. Vegetables (tomatoes, Nakati, cabbages)

8. For how long have you been growing coffee? ……………………………………… 9. Have you received any informal education in coffee agroforestry? 1. Yes 2. No

10. If yes, what was the source? ……………………………………………………………………

Investigating the coffee farm for coffee cultivation systems

11. What is your source of labor for managing the coffee farm? (More than one possible) 1. Family labor 3. Hired labor 2. Helping each other 4. Others (specify) ……………..

71

12. Fill the table below on type of robusta coffee grown and reasons why. Variety (more than 1 possible) Age Reasons (>1 possible) Comment 1. Traditional 2. Clonal (cutting, elite) 3. Mixed

13. What type of inputs do you invest in coffee production? 1. Fertilizers 6. Manure 2. Machines 7. Coffee seedlings (specify) 3. Tree seedlings (specify) 8. Equipments (specify) 4. Insecticides/fungicides 9. Others (specify) ……….. 5. Fungicides

Assessing farmers’ criteria for Agroforestry tree species selection

14. Do you know of any tree nursery in your nearby area? 1. Yes 2. No

15. How far is the tree nursery known to you located? ……………………………..

16. Please specify details of agroforestry trees grown or retained on your coffee farm Tree species Most Establishment (e.g. Source (e.g. own nursery Origin (tick where grown seedlings, wildings, own farm, gov’t, NGO, applicable) (please rank) cuttings) Neighbour, purchase, etc.) Exotic Indigenous

17. Why do you grow or retain these tree species? (More than one possible but probe further for the main reason) 1. Improve soil fertility 4. Shade for coffee 2. Products for home use 5. Products for sale 3. Increased quality of coffee 6. Others (specify) ……………….

18. What tree attributes do you consider in selecting tree species to plant in your coffee? 1. Enough shading habits 5. Ability to add nutrients to the soil 2. Fast growing 6. Ability to produce diverse products 3. Compatibility with coffee 7. Low management requirement 4. Risk diversification 8. Others (specify) …………….

Assessing farmers’ perceptions on agroforestry tree species

19. What are the advantages of using agroforestry tree species in coffee farms? 1. Improved production of coffee 4. Associated products from trees are higher 2. Improved soil nutrients 5. Improved coffee quality 3. Reduction of pests and disease 6. Others (specify)……………………………..

20. Would you like to plant more trees in your coffee? 1. Yes 2. No

72

21. If yes, which tree species would you like to plant in your coffee?

22. Have you any hindrances in planting your preferred tree species in the coffee farm? 1. Yes 2. No

23. If yes, what hinders you from planting the required tree species? 1. Lack of planting material 5. They take a long time to grow 2. Require a lot of labor 6. Lack of knowledge 3. Small farm sizes 7. Others (specify) ………………………… 4. Negative effects on coffee (specify)

24. Please complete the table below on tree species grown on your coffee farms Tree species Tree function (more than one possible) Individual tree attribute

25. What are the main tree products harvested? Tree species Main tree products Use (tick) Commercial Non-commercial

26. What management practices do you perform on tree species planted on coffee farms?

27. Please specify reasons for the management option

Farmers’ observation of tree-crop competition and strategies to reduce it

28. What positive effects of trees on coffee have you identified? 1. Windbreaks 4. Hosts to natural enemies 2. Microclimate 5. Water conservation 3. Nutrient addition 6. Others specify ………….

29. How do you increase the positive effects? ………………………………….

30. What negative effects of trees on coffee have you identified? 1. Competition for nutrients 4. Source of pests and diseases 2. Competition for water 5. Others specify ………….. 3. Competition for light

31. How do you reduce the negative effects? ……………………………………

On-farm observation: Investigating coffee agroforestry cultivation systems

32. Please specify the level of management of the coffee farm

73

3.3. What are the components of the coffee farm? 1. Coffee + trees 3. Coffee + Trees + seasonal crops 2. Coffee + banana + Trees 4. Others specify ......

34. Complete the table on management priority and vertical niche occupied by each component. Code Main components Rank (according to management priority) Vertical niche

34. Discussion on the crop combinations being practiced by the coffee farmer on the coffee farm Crop combination comment Productivity rank of the system Reasons for the rank (if more than 1)

35. Further investigation of the woody component. Tree species Arrangement Spacing (specify) Reasons for arrangement and spacing Regular Irregular

38. Complaints on some of the tree species being grown on the coffee farm and key observations on farm

74

B. Questionnaire for Key informants Position of the interviewee: Date of discussion:

1. How long have you been staying/working in this area?

2. What is your main occupation?

3. What are the main sources of income in this area? Source Yes/No Ranking (1= No.1) Remark Agriculture Livestock Fuel wood Charcoal production Non- wood tree products Fishing Trading Official employment Others, specify ….

4. How important is coffee to the farming households in this area?

5. Which type of coffee is grown here?

6. In which ways does coffee production now differ from coffee production 10 years ago?

7. Which are the most common tree species grown with coffee in this area?

8. Why do you think these trees are grown in coffee?

9. Are the tree products preferably consumed at home or sold in the market?

10. What are some of the constraints faced by farmers in selecting tree species to plant in their coffee?

11. How can these constraints be overcome?

12. What are some of the tree species that are being promoted here for coffee agroforestry?

13. How do you comment on their adoption comparing both indigenous and exotic trees species?

14. What do you think is the preference of farmers between exotic and indigenous tree species?

15. What are the reasons for this preference?

16. How would you categorize the coffee cultivation systems in this area?

75

C: Questionnaire for research institutions

Position of the interviewee: Date of discussion: Location:

1. What is the role of your organization in coffee production in Uganda?

2. To what extent has your organization fulfilled this role?

3. How would you categorize the coffee cultivation systems in Uganda?

4. What challenges are facing the development of coffee agroforestry in Uganda?

5. Which are the most common tree species grown by farmers with coffee and why? Tree species Reason

6. Which tree species does your organization promote for coffee agroforestry and why? Tree species Reason

7. What are some of the limitations faced in promoting such tree species?

8. What are some of the constraints faced by farmers in selecting tree species to plant in their coffee?

9. How can these constraints be overcome?

10. What do you think is the preference of farmers between exotic and indigenous tree species?

11. What are the reasons for this preference?

12. Please provide any other remarks on coffee agroforestry in Uganda

76

Appendix 2: Some of the trees and shrubs which were promoted by SCC-Vi Agroforestry project in the study area

Scientific name Local name Scientific name Local name Acacia mearnsii Bulikoti Podocarpus latifolius Musenene Albizia chinensis Mugavu muzungu Polyscias fulva Ssetala Albizia coriaria Mugavu muganda Senna siamea - Albizia lebbeck - Sesbania sesban Muzimba ndegeya Azadirachta indica Nimu Spathodea nilotica Kifabakazi Cajanus cajan Mpinnamiti Tamarindus indica - Calliandra calothyrsus Kalibwambuzi Tephrosia vogellii Muluku Callistemon citrinus Nyambade zitonya Terminalia brownii Muyati Casuarina equisetifolia Kalivaliyo Terminalia mantaly - Cedrella odorata - Termonalia superba - Chlorophora excelsa Muvule Prunus africana Ngwa buzito Cordia africana Mukebu Carica papaya Mupaapali Ficus natalensis Mutuba Psidium guajava Mupeera Grevillea robusta Kalwenda Persea americana Ovakedo Khaya anthotheca Munyama Mangifera indica Muyembe Maesopsis eminii Musizi Citus sinensis Muchungwa

Syzygium cumini Jambula Artocarpus Yakobo, Kifenensi, Ffene heterophyllus Markhamia lutea Musambya Moringa oleifera Moringa

Melia azedarach Lira, Muttankuyege Gliricidia sepium -

Source: Adapted from SCC-Vi Agroforestry database (2011)

77

Appendix 3: Plates

Plate 1: Management of trees in the banana coffee intercropping system

Plate 2: Comparison of leaf decomposition. A: Poor leaf decomposition under Artocarpus heterophyllus B: Very fast leaf decomposition under Albizia chinensis

78

Plate 3: Linking Ficus natalensis to the CWD. Circles: Removal of Ficus natalensis. Arrows: Replanting to replace those coffee plants affected by CWD

Plate 4: Susceptibility to wind and storm

79