Cropping System and Altitude As Drivers of Soil Macrobiota and Nutrient Variability for Arabica Coffee Production in Mount Elgon Region

CROPPING SYSTEM AND ALTITUDE AS DRIVERS OF SOIL MACROBIOTA AND NUTRIENT VARIABILITY FOR ARABICA COFFEE PRODUCTION IN MOUNT ELGON REGION

SCOLA CHERUKUT

B.Sc. AGRIC (MAK)

REG. NO: 2015/HD02/496U

A THESIS SUBMITTED TO THE DIRECTORATE OF RESEARCH AND GRADUATE TRAINING IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR AWARD OF THE DEGREE OF MASTER OF SCIENCE IN CROP SCIENCE OF MAKERERE UNIVERSITY

DECEMBER, 2018

DEDICATION

I dedicate this work to God, my parents Mr. Nelson Kusuro and Mrs. Jesca Kusuro, and to my brothers and sisters for their support in my career development.

ACKNOWLEDGEMENTS

I thank the Almighty God for giving me knowledge, wisdom and good health to conduct this study. I am highly grateful to RUFORUM that provided tuition, stipend and research funds and, the Africa initiative of the Volkswagen Foundation through the project on Productivity and biological diversity in the coffee-banana system in the Mt. Elgon Region of Uganda: Establishing Trends, Linkages and Opportunities, for additional research funds. In the same respect, I thank the farmers of the Mount Elgon region especially the districts of Kapchorwa and Sironko where the research was carried out.

I am greatly indebted to Assoc. Prof. Jeninah Karungi and Dr. John Baptist Tumuhairwe for their professional guidance and mentorship. May God richly bless you! I thank my parents Mr. and Mrs. Nelson Kusuro, my brothers and sisters for their love and support, this has always kept me going. It cannot go without mention the support and constant prayers of my dear friends Orapa Nicholas Ijala Tony, Chemonges Martin, and Ayot Phoebe. There are many other people I may have not mentioned but I am grateful for all you have done for this project. May God richly bless you all!

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TABLE OF CONTENTS

DECLARATION ...... i DEDICATION ...... ii ACKNOWLEDGEMENTS ...... iii TABLE OF CONTENTS ...... iv LIST OF TABLES ...... vii LIST OF FIGURES ...... viii LIST OF APPENDICES ...... ix ABSTRACT ...... x CHAPTER ONE ...... 1 Introduction ...... 1 1.1 Background ...... 1 1.2 Problem statement ...... 2 1.3 Justification of the study ...... 4 1.4 Study objectives ...... 4 1.4.1 General objective ...... 4 1.4.2 Specific objectives ...... 5 1.5 Hypotheses ...... 5 CHAPTER TWO ...... 6 Literature Review...... 6 2.1 Coffee agronomy and ecology ...... 6 2.2 Overview of coffee production constraints ...... 6 2.3 Ecosystem services and their drivers in agro-ecosystems ...... 7 2.4 Root mealybug (Hemiptera: Pseudococcidae) as a pest of coffee ...... 8 2.4.1 Description of root mealybug ...... 8 2.4.2 Biology and ecology of the root mealybug ...... 8 2.4.3 Damage caused by the root mealybug ...... 9 2.4.4 Management of the root mealybug ...... 9 2.5 Soil dwelling macrofauna in coffee systems ...... 10 2.5.1 Earthworms (Lumbricidae: Oligochaeta) ...... 10 2.5.2 Millipedes (Myriapoda: Diplopoda) ...... 12

2.5.3 Ants (Hymnoptera: Formicidae) ...... 12 2.6 Effect of cropping system on soil properties and coffee productivity ...... 14 2.7 Effect of altitude on soil properties and coffee productivity ...... 15 CHAPTER THREE ...... 16 Materials and Methods ...... 16 3.1 Description of study sites ...... 16 3.2 Study design ...... 16 3.3 Data collection ...... 17 3.3.1 Root mealybug ...... 17 3.3.2 Soil properties and microclimate ...... 17 3.3.3 Coffee yield ...... 19 3.4 Data analysis ...... 19 CHAPTER FOUR ...... 20 Results ...... 20 4.1 Effect of cropping system and altitude on root mealybug severity ...... 20 4.2 Effect of cropping system and altitude on soil properties and microclimate ...... 20 4.2.1 Abundance of earthworms ...... 20 4.2.2 Abundance of millipedes ...... 21 4.2.3 Abundance of ants...... 22 4.2.4 Effect on soil moisture and temperature ...... 23 4.2.5 Effect on soil chemical properties ...... 24 4.2.6 Effect of cropping system and altitude on microclimate ...... 29 4.3 Effect of coffee cropping system and altitude on coffee yield indicators ...... 30 4.3.1 Effect on number of fruiting nodes per branch ...... 30 4.3.2 Effect on number of berries per branch ...... 31 CHAPTER FIVE ...... 32 Discussion ...... 32 5.1 Effect of cropping system and altitude on the root mealybug ...... 32 5.2 Effect cropping system and altitude on soil properties and microclimate ...... 32 5.2.1 Effect cropping system and altitude on earthworms ...... 32 5.2.2 Effect cropping system and altitude on millipedes ...... 33

5.2.3 Effect cropping system and altitude on ants ...... 33 5.2.4 Effect cropping system and altitude on soil organic matter and total nitrogen ...... 34 5.2.5 Effect cropping system and altitude on soil temperature and moisture ...... 34 5.2.6 Effect cropping system and altitude on ambient air temperature and relative humidity ..... 35 5.3 Effect of cropping system and altitude on coffee yield indicators ...... 35 CHAPTER SIX ...... 37 Conclusions and Recommendations ...... 37 6.1 Conclusion ...... 37 6.2 Recommendations ...... 37 REFERENCES ...... 38 APPENDIX ...... 51

LIST OF TABLES

Table 1: Soil pH, available P (ppm), K, Na, Ca, and Mg (cmol+ kg-1) under cropping system at different altitudes (0 -15cm soil depth) ...... 28 Table 2: Soil pH, available P (ppm), K, Ca, Mg and Na (cmol+ kg-1) under cropping system at different altitudes (15 - 30 cm soil depth) ...... 28

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LIST OF FIGURES

Figure 1: Effect of cropping system and altitude on coffee root mealybug severity ...... 20 Figure 2 : Effect of cropping system at different altitudes on number of earthworms ...... 21 Figure 3: Effect of altitude on number of millipedes ...... 21 Figure 4: Effect of cropping system on number of millipedes ...... 22 Figure 5: Effect of cropping system on number of ants...... 22 Figure 6: Effect of altitude on number of ants ...... 23 Figure 7: Effect of cropping system at different altitudes on soil moisture...... 23 Figure 8: Effect of cropping system at different altitudes on soil temperature ...... 24 Figure 9: Effect of cropping system on soil organic matter at soil sampling of 0 - 15cm ...... 25 Figure 10: Effect of altitude on soil organic matter ...... 25 Figure 11: Effect of cropping system on total nitrogen at soil sampling depth of 0 - 15cm ...... 26 Figure 12: Effect of altitude on total nitrogen at soil sampling depth of 0 - 15cm ...... 26 Figure 13: Correlation between soil organic matter and total nitrogen ...... 26 Figure 14: Effect of cropping system on ambient temperature...... 29 Figure 15: Effect of altitude on ambient air temperature in coffee plantations ...... 29 Figure 16: Effect of altitude on relative humidity in coffee plantations of Mt. Elgon ...... 30 Figure 17: Effect of cropping system at different altitudes on number of fruiting nodes per branch ...... 31 Figure 18: Effect of cropping system at different altitudes on the number of berries per branch 31

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LIST OF APPENDICES

Appendix 1: Soil organic matter as influence by cropping systems at different altitudes in Mt. Elgon region of eastern Uganda (interactions) ...... 51 Appendix 2: Percentage Nitrogen as influenced by cropping systems at different altitudes in Mt. Elgon region of eastern Uganda (interactions) ...... 51 Appendix 3: Analysis of variance tables for soil fauna ...... 52 Appendix 4: Analysis of variance tables for microclimate ...... 52 Appendix 5: Analysis of variance for coffee yield ...... 53 Appendix 6 : ANOVA tables for soil nutrients at soil depth of 0 - 15cm ...... 54 Appendix 7: Soil nutrients at soil - soil depth of 15-30cm ...... 56

ABSTRACT

There is need to produce sufficient food and fuel for the growing population without damaging the ecosystem services. In Uganda, highlands have inherent fertile soil but are rapidly losing quality due intensification. Farmers utilize various management adaptations such as agroforestry systems with other on-farm soil, pest and disease management practices to increase production. A study was carried out to determine how different coffee cropping systems at varying altitudes influence occurrence of the soil dwelling coffee root mealybugs, nutrient cycling macro-fauna, soil nutrients, microclimate, and yield of coffee in the Mt. Elgon Region (MER) of Uganda. The factors investigated were altitude and cropping systems. Three levels of altitude were considered namely; i) low (1300-1499 meters above sea level (m.a.s.l), ii) mid (1500-1679 m.a.s.l) and iii) high (1680- 2100 m.a.s.l). Cropping system was demarcated into four categories; i) Coffee monocrop, ii) Coffee-annual crop, iii) coffee-banana, and iv) coffee-banana-shade trees, which were nested within the altitude categories. Data was collected on longitudinal basis on abundance of root mealybugs (Pseudococcidae), ants (Formicidae), millipedes (Diplopoda), and earthworms (Lumbricidae) in the fields. Ambient temperature and relative humidity were obtained on a monthly basis in the study fields. Soil temperature and moisture were taken in situ using sensors. Composite soil samples from the fields were taken for analysis of selected physical and chemical properties. Results showed that cropping system, altitude and their interaction significantly influenced the occurrence of the arthropods in the different functional groups. Soil macrofauna were greatly influenced by cropping system and altitude; earthworms preferred the cooler and more diversified cropping systems while millipedes were common in nitrogen richer soils. Root mealybugs were more severe in coffee monocrops than in shaded systems. The coffee-annual crops systems had low abundance of soil macrofauna, nutrients, high severity of the root mealybug and relatively warmer microclimate. Coffee systems intercropped with shade trees and bananas had cooler temperatures and higher relative humidity. It was noted that more diverse intercrops gave higher coffee berry yields, even at higher altitudes. Diversified coffee systems had enriched soil biota, higher concentrations of soil organic matter and total nitrogen and high moisture content and low soil temperature. This showed that the diversified coffee systems were more linked to soil conservation and productivity, which is crucial in highland areas like the Mt. Elgon region.

CHAPTER ONE Introduction

1.1 Background Coffee is one of the top beverages in the world and a most valuable export crop (Jassogne et al., 2013). It has an annual global retail value of approximately US $ 90 billion (DaMatta et al., 2007; Jaramillo et al., 2011). Over the last 50 years, there has been a steady growth in world coffee production although with periodic falls (International Coffee Organization, 2014) like in 2014 when global coffee production declined by 2.08 % (ICO, 2017) due to the effects of climate change (Barros et al., 2014). In Africa with the exception of Ethiopia and Uganda, coffee production has experienced a downward trend in the past 50 years, registering less than 20 million bags every year since 1990 (ICO, 2014). This has lowered Africa’s share in world production of coffee from 25 % to 14 % (ICO, 2014).

Coffee is an important source of foreign exchange earnings in east and central Africa (Rutherford, 2006). Uganda is the second largest producer of coffee in Africa with over half a million households depending on coffee for their livelihood (Van Asten et al., 2011). Uganda has had a sustained growth in its production, with an annual average of 2.9 million bags since 1990 (ICO, 2014). There was a tremendous increase in coffee yield from 219,000 tons in 2015 to 294,000 tons in 2016 amounting to 34.2 % increase in production (ICO, 2017). Approximately 40 % of coffee export value in Uganda is attributed to Arabica coffee (Coffea Arabica) though significant inter- annual variations occur depending on crop yields and price fluctuations (Jassogne et al., 2013). Arabica coffee is more competitive on the international market because of its superior flavor and quality (Rutherford and Phiri, 2006).

It is important to note that although Uganda’s coffee exports has gradually increased over the years, this is mainly attributed to the expansion of the coffee growing areas within the country. The Uganda Coffee Development Authority (UCDA) set a target of increasing coffee exports to 4.5 million tons by 2015 and the main strategy was to expand area under coffee by distributing free seedlings in different regions. Conversely, there has been an overall decrease in the yield from the existing old coffee trees. This decline is due to a combination of several factors including climate change variability, declining soil fertility, ravages of pests and diseases, poor crop and land

1 management arising from market uncertainties (Jonsson et al., 2014). Yet, suitable land use management options such as appropriate cropping systems have the opportunity of improving ecosystem services and enhancing coffee yields and thereby offering relief from environmental shocks and improving farmer livelihoods.

Notably, productivity of crops depends on an intricate interplay of farming practices, abiotic conditions and ecosystem services provided by natural species communities (Classen et al., 2014). Arabica coffee is predominantly grown in highlands such as on the slopes of Mount Elgon, Mt. Rwenzori and Mt. Muhavura, and areas above 1400 m.a.s.l (Jassogne et al., 2013). Mountainous ecosystems are subject to both natural and anthropogenic drivers of change which include; volcanic and seismic events, global climate change, loss of vegetation and soil due to agricultural and forestry practices. And yet the recovery of these ecosystems is typically slow or does not occur due to the sloping terrain and relatively thin soils (Korner et al., 2005). Human activities have resulted in simplification of agro-ecosystems to favor those species that give direct benefits while overlooking the unseen but yet very essential ecosystem services (DEWHA, 2009).

However, proper agricultural management has the potential to enhance biodiversity and ecosystem functions (Rosenzweig, 2003). For example, coffee agroforestry shaded by a diversity of natural or planted trees represents a forested habitats which supports a large biodiversity (Perfecto and Armbrecht, 2003).Coffee is mainly grown by smallholder farmers (Mafusire et al., 2010) as a monocrop or an intercrop with banana or other traditional food crops and shade trees (Jassogne et al., 2013). Coffee–banana intercropping is common in densely populated areas (Van Asten et al., 2011), and coffee is usually grown with shade on the lower slopes and without shade on the highest slopes (Soini, 2007).

1.2 Problem statement In Uganda, studies have shown that Mount Elgon region area is among the severely degraded in East Africa (Knapen et al., 2006; Mugagga et al., 2013), yet it is the leading producer of arabica coffee. This is believed to be a result of land use change where large areas of landscape catchments of natural vegetation have been converted to agricultural fields. Lately, these converted agricultural field are not sustainably managed, leading to land degradation. Changes and loss of biodiversity directly influences the capacity of an ecosystem to produce and supply essential

2 services, and affects the long term ability of ecological, economic and social systems to adapt and respond to global pressures (DEWHA, 2009). Species combination which forms the structure of an ecosystem is important in determining the capacity of an ecosystem to produce services. Therefore conserving or restoring the structure rather than just maximizing species numbers, is critical to maintaining ecosystem services.

Clearing of natural vegetation causes decline in biodiversity thus affecting the functioning of natural pest control because non-crop habitats provide requisites for a broad spectrum of natural enemies (Tscharntke et al., 2005; Bianchi et al., 2006). Pests and diseases are responsible for losses of approximately 30 - 40 % of the total coffee production (Perfecto, 2007) and more so in arabica coffee (Rutherford and Phiri, 2006). Karungi et al. (2015) noted that root mealybugs have become a common problem in the coffee growing region of Mt. Elgon. This pest which is known to cause severe damage in coffee, is more prevalent in nutrient-deficient soils (Rutherford and Phiri, 2006). The root mealybugs multiply rapidly in low soil moisture conditions (Barrera, 2008). Yet management practices alter and influence nutrient availability and the soil microclimate. Similarly, abundance of soil macro-fauna communities are very sensitive to the management of the soil cover (Barros et al., 2002).

It should be noted that farmers have utilized traditional resource management adaptations, such as agroforestry systems with other soil, pest and disease management practices (Jassogne et al., 2013) to maintain highland ecosystems services and products. However, repeated episodes of ecosystem degradation have been reported. In the Mt. Elgon region, there is a progression in coffee cropping systems from more diverse systems incorporating shade trees and or bananas to coffee monocrop systems (Jassogne et al., 2013). It was noted that coffee cultivation under agroforestry systems is advantageous compared to coffee grown in full sun monoculture (Siles et al., 2010). However, Avelino et al. (2007) explained that shade can result in a humid micro-environment conducive to higher incidence of fungal diseases especially at high altitude and also reduces coffee flowering intensity. Therefore, the most profitable and yet sustainable coffee based cropping system is not known.These cropping systems are positioned at different altitudinal ranges within the mountain slope with unknown effects on soil properties. Furthermore, it is not clear how the cropping systems and altitude interact to drive sustainability of soils and pest control systems in the coffee growing areas of Uganda.

1.3 Justification of the study The current challenge in the Mt. Elgon region like the rest of the world is to meet the food and fuel demands of a growing population by enhancing the productivity of the local agricultural systems without damaging the ecosystem services provision. This can be achieved if the focus is put on assessing the effects of resource use and management in agricultural systems on the dynamics and value of ecological services delivered from the greater socio-ecological systems they are embedded in. Any changes in the land use and management impacts on the capacity of an ecosystem to produce and supply essential services, and can affect the long term ability of agro- ecosystems to adapt and respond to global pressures (DEWHA, 2009).

Sustainable utilization of the ecosystems is vital for survival of natural enemies for control of pests and diseases especially for coffee. Naturally occurring or indigenous natural enemies prevent many plant-feeding insects from achieving pest status (Charlet et al., 2002) yet effective conservation of natural enemies depends on understanding the agro-ecosystem (Rice, 2010). Furthermore, arabica coffee production is reduced by increase in temperatures (Haggar and Schepp, 2011) and nutrient deficiency (Mendonça and Stott, 2003). Proper agricultural management has the potential to enhance biodiversity and ecosystem functions (Tscharntke et al., 2005). Coffee in agroforestry can provide favorable environment for maintenance of biodiversity, watershed services, soil fertility, natural enemy conservation and resilience to climate change effects through creating a suitable microclimate (Jassogne et al., 2013).

Furthermore, ecosystem services and biodiversity conservation in coffee systems have frequently been studied in isolation from coffee productivity. Understanding the contribution of various agricultural practices to the range of ecosystem services would help inform choices about the most beneficial agricultural practices (Dale and Polasky, 2007). Efficient and effective management of these agro-ecosystems can sustain the provision of vital ecosystem services (Millennium Ecosystem Assessment, 2005).

1.4 Study objectives 1.4.1 General objective To enhance productivity of the Mount Elgon coffee systems and improve ecosystem services provision through development of recommendations for sustainable ecological approaches of land resources.

1.4.2 Specific objectives i. To evaluate the influence of cropping system and altitude on the occurrence of the soil dwelling root mealybug in the coffee production systems of the Mt. Elgon Region. ii. To evaluate the influence of cropping system and altitude on abundance of selected soil macro-fauna, nutrient availability, and microclimate in coffee production systems of the Mt. Elgon Region iii. To evaluate the influence of cropping system and altitude on the yield of Arabica coffee in the coffee production systems of the Mt. Elgon Region

1.5 Hypotheses i. Coffee grown with banana and shade trees will have low root mealybug occurrence irrespective of the altitude. ii. Soil properties and microclimate of a given coffee field are dependent on the cropping system and altitude gradient. iii. Shaded coffee systems give better yield performances at lower altitude than at high altitudes.

CHAPTER TWO Literature Review

2.1 Coffee agronomy and ecology Arabica (Coffea arabica) and Robusta (Coffea canephora) are the two types of coffee grown in Uganda contributing 10 % and 90 % of production in Uganda, respectively (Masiga and Ruhweza, 2007). However, Arabica coffee contributes more than 60 % of global coffee production and this is because the species is considered to produce beans of higher quality and therefore attracts a higher market value (Rutherford and Phiri, 2006). Robusta is grown in the lower altitudes, up to 1,200 meters above sea level (m.a.s.l), while Arabica is grown at higher altitudes of 1,400 - 2,300 m.a.s.l (Masiga and Ruhweza, 2007; Ahmed, 2012). Arabica coffee requires a cool tropical climate (COMPETE, 2002) that is only found in high altitude areas such as areas of Mt. Elgon along Uganda’s eastern border with Kenya and in south-western Uganda along the Rwenzori mountain range (Ahmed, 2012). There is a potential for over a half million hectares of Arabica in Uganda yet currently less than 9 % of its biophysical potential production area for Arabica is being utilized (UCDA, 2012). Coffee is cultivated under various management schemes from heavy shade of trees or bananas to full sun monocrops (Siles et al., 2010; Ahmed, 2012).

Arabica coffee is a tropical plant, which belongs to the family Rubiaceae and genus Coffea. It can grow to a height of 10 - 15 m at maturity, but is kept at 3 m in plantations for harvesting purposes. The shrubs remain productive for 15 - 20 years. It requires average temperature ranges of 12 - 26 °C although it can tolerate temperatures well outside this range. However, extreme temperature variation usually affects the crop and the coffee bush. Warmer temperatures are necessary for proper fruit development and ripening. Coffee is sensitive to water shortages and requires adequate well-distributed precipitation of about 1500 mm per annum. Adequate rainfall increases flowering and berry weight (Munyuli, 2011; Jassogne et al., 2013)

2.2 Overview of coffee production constraints Coffee yields in Uganda are far below potential due to various biotic, abiotic, and management constraints (Wang et al., 2014). Secondly, the increase in population and land use pressure have reduced available land needed to expand area under coffee production. Other constraints include

6 poor soil fertility in almost all regions, erratic rainfall, poor management practices (especially unproductive coffee trees, low coffee density, and lack of mulching), and pests and diseases being the primary reason responsible for coffee yield reduction. Pests and diseases are responsible for losses of approximately 30 – 40 % of the total coffee production in Uganda (Perfecto, 2007; Lin, 2010). Arabica coffee is more susceptible to pests and diseases than robusta coffee (Kimani et al., 2002; Rutherford and Phiri, 2006). This study will focus on how cropping systems and altitude drive the abundance of the soil dwelling root mealybugs.

2.3 Ecosystem services and their drivers in agro-ecosystems The contribution of ecosystems to human wellbeing is normally referred to as “ecosystem services” (Dale and Polasky, 2007). Some of the essential ecosystem services include; water quality, pollination, nutrient cycling, pest control, soil retention, carbon sequestration, and biodiversity conservation (DEWHA, 2010), which in turn affect agricultural productivity. However, the benefits differ based on the ecosystems’ sensitivity and resilience to degradation (Mugagga et al., 2012; Jiang and Pilesjö, 2014). Mountain ecosystems are the most fragile, highly sensitive to degradation yet have low resilience. Most of the highlands in East Africa have considerably inherent fertile soil due to the young volcanic soil and are sources of water points making them suitable for agriculture. However, soils in highlands are rapidly losing their quality as a result of intensification. The consequence is reduced ability to meet food and fuel demands of growing human populations (WinklerPrins and Sandor, 2003; Jaramillo et al., 2011).

Soils are involved in the provision of many ecosystem services that are of great importance for the maintenance of ecosystem functioning and human societies, with farmers primarily responsible for the management of this resource (Millennium Ecosystem Assessment, 2005; Wall et al., 2012). Soils are also considered a large reservoir of biodiversity that has received less attention relative to above ground communities (Wall et al., 2012). Soil macrofauna, in particular, represent an important part of agro-ecosystem biodiversity and some groups have received considerable attention as ecosystem engineers that fundamentally influence the nature and functioning of soils they inhabit (Lavelle et al., 2006). Past research indicates that the loss of soil macro-invertebrate diversity degrades soil structure and diminishes nutrient cycling (Velásquez et al., 2012).

Arabica coffee systems in Mt. Elgon area are characterized by natural and semi natural vegetation and this mitigates the negative effects of tree loss and can complement the protection of forest ecosystems. Coffee agroforestry can provide maintenance of biodiversity, watershed services, soil fertility, natural enemy conservation and resilience to climate change effects through creating a suitable microclimate (Jassogne et al., 2013).

2.4 Root mealybug (Hemiptera: Pseudococcidae) as a pest of coffee

2.4.1 Description of root mealybug Mealybugs can attack the aerial parts of coffee. However mealybugs mostly occur on roots referred to as root mealybugs and are among the most important mealybugs of coffee in Africa (Rutherford and Phiri, 2006). Mealybug lay small eggs of about 0.5 mm. The nymphs are oval, slightly swollen, usually white, yellow or pink colored, and covered by a white waxy-mealy dust with waxy filaments projecting laterally. The adult females have no wings, and are similar to the nymphs but larger. Males are white, fragile-looking, smaller than the females, and they possess a pair of wings and a pair of terminal filaments (Franco et al., 2004; Barrera, 2008).

2.4.2 Biology and ecology of the root mealybug The most harmful species are Dysmicoccus bispinosus, D. brevipes, Neorhizoeccus coffeae, Geococcus coffeae and Chavesia caldasiae (Rutherford and Phiri, 2006). Mealybugs multiply rapidly, especially in dry weather and their numbers are reduced by prolonged or heavy rainfall. A single female may deposit between 300 - 600 eggs although the females die shortly after the eggs hatch. The life cycle from egg to adult takes 30 - 120 days, varying according to the species and ambient temperature. Upon eclosion, the small nymphs start looking for an appropriate place to settle on the plant root where they insert their mouthparts to feed. Depending on the type of soil, the humidity, aeration and age of the coffee plant, they usually place themselves between 10 - 60 cm under the soil surface and their population diminishing as the soil depth increases (Barrera, 2008). Different species prefer different parts of the root. For example, D. brevipes prefer the main and the lateral roots while G. coffeae attacks the absorbent roots but the smaller species attack the whole root system near the soil surface (Franco et al., 2004). The coffee root mealybug is usually associated with a soil fungus, Diacanthodes novoguineensis (also known as Polyporus coffeae) and ants (Formicidae) (Rutherford and Phiri, 2006; Barrera, 2008).

2.4.3 Damage caused by the root mealybug Root mealybugs have been known to cause severe damage to coffee (Rutherford and Phiri, 2006; De Souza et al., 2007). Mealybugs feed on the plant by puncturing the plant tissues with a stylet and sucking the sap (Rutherford and Phiri, 2006; Barrera, 2008). In case of serious attacks by Dysmicoccus bispinosus, a thick, cork-like, dark crust covers the main and secondary roots which causes the attacked roots to lose their absorbent root hairs. This damage creates a general condition of weakness, slow growth, and heavily attacked plants perish. The attacked plants have little anchorage and are easily dislodged. The symptoms may be confused with the symptoms of fungal diseases and with physiological plant problems (Barrera, 2008). Damage is more apparent on nutrient-deficient soils and where weeds are abundant. The varieties of Arabica coffee grown in Uganda are susceptible to mealybug attack. Root mealybugs are polyphagous, attacking other plants such as shade trees (Inga spp.), cassava (Manihot esculenta), sugarcane (Saccharum sp), banana trees (Musa sp), lemon trees (Citrus sp) and some herbs that grow within the coffee plantation (Rutherford and Phiri, 2006; Barrera, 2008).

2.4.4 Management of the root mealybug Root mealybugs are very difficult to detect and control. Therefore, preventing their spreading and establishment is paramount. Preventative measures include use of clean planting material, removal of alternate host plants, prevention of irrigation water from infested areas, and disposal of the infested plant debris. Banana suckers are suspected to be the possible source of infestation in coffee banana intercrops, therefore spread of the root mealybug is to be checked by prevention of use of suckers from the mealybug infested areas (Mani et al., 2016).

Adequate fertilization should be provided, including addition of organic matter to the soil. Planting coffee trees on land previously supporting plants that are highly susceptible to mealybugs (cassava, sugarcane) should be avoided. Severely damaged plants should be removed and burned (Barrera, 2008). Control with chemicals is not easy because the root mealybug are present on the roots of the plant and the presence of the protective wax and the fungal layer (Rutherford and Phiri, 2006; Hara et al., 2001).

2.5 Soil dwelling macrofauna in coffee systems The progressive accumulation of organic materials is characteristic of the development of most soils and depends on the activity of a wide range of microbes, plants and associated organisms (Lavelle and Spain, 2001). Soil fertility is important for good coffee production (Kimani et al., 2002). Detritivores form an integral component of ecosystems, and include diverse taxa of invertebrates such as isopods, amphipods, millipedes, oribatid mites, dipteran larvae, earthworms and collembolans (Paoletti et al., 2007). Detritivores are abundant in soils and are responsible for litter decomposition by fragmentation, comminution, seasoning, digestion and conditioning of organic matter (Lavelle and Spain, 2002; Greenslade, 2007).

Cropping systems influence soil biota predominately through the kind and quantity of plant residue food sources they provide, and their impacts on the soil physical and chemical environment (Liebig et al., 2005). Soil invertebrate communities vary according to the amount and quality of organic matter inputs (Lavelle and Spain 2001). For these reason, they are very useful for assessing disturbance over time and for comparing different landscape management practices (Paoletti et al., 2007). Therefore unravelling how these important soil organisms are deterministically structured by abiotic and biotic factors is of utmost relevance in fostering favorable environments for their increased abundance and action. This study will concentrate on three representative soil inhabiting macrofauna including earthworms, millipedes and ants.

2.5.1 Earthworms (Lumbricidae: Oligochaeta) Earthworms act as the bio-indicators of soil quality (Crittenden et al., 2014). They also provide several beneficial ecosystem services and it is for these reasons that focus has been given to earthworms in agriculture management. There is need of knowing the distribution of earthworms, factors affecting their distribution and how they contribute in modification of soil environment.

Earthworms are macrofauna clitellate oligochaete annelids that live in soil. They are segmented worms, bilaterally symmetrical, with an external gland (clitellum) for producing the egg case (cocoon), a sensory lobe in front of the mouth (prostomium), and an anus at the end of the body, with a small number of bristles (setae) on each segment (Dominguez and Edwards, 2011). Earthworms burrow continually through the soil; each body segment possesses both a circular and

10 a longitudinal musculature. They are nonselective deposit feeders. Ingestion of organically enriched soil is accomplished by the pumping action of the pharynx, (Paul and Clark, 1996).

Different species of earthworms have different life histories, occupy different ecological niches, and have been classified, on the basis of their feeding and burrowing strategies, into three ecological categories: epigeic, anecic, and endogeic (Dominguez and Edwards, 2011). Anecic earthworms dig vertically oriented galleries that extend to depths greater than 1 m in the soil profile. Endogeic earthworm galleries are not preferentially oriented in the vertical direction. The burrow diameter is smaller than anecic burrows, and they are not so deep. Epigeic earthworms remain in the litter layer and in the first few centimeters of the soil and thus have little effect on soil macro-porosity (Bertrand et al., 2015).

Earthworm species richness, size, structure of populations and their biomass are dependent on crop management (Riley et al., 2008; Pelosi et al., 2009). A number of factors affect earthworm growth and survival; these include tillage, fertilization, soil carbon inputs, and soil texture (Marhan and Scheu, 2005). According to Chan (2001) review, the effect of tillage on earthworm populations depends on the earthworm functional group as well as the tillage implement and intensities used. Tillage tends to reduce populations of especially anecics which are abundant on litter. Some pesticides and simplification of crop sequence, elimination of ecological infrastructures also have a negative impact on earthworm populations (Bertrand et al., 2015). Crop diversity, hedges, and land use have an influence on the spatial distribution of earthworm species although limited research has been done in this area. This is the motivation behind this research to evaluate how different cropping systems with interact of altitude affects abundance of earthworms in coffee agro-ecosystems.

Earthworms play an important role in many soil functions in agricultural soils (Crittenden et al., 2014). Earthworms affect soil properties in agro-ecosystems such as; nutrient availability, soil structure, and organic matter dynamics (Edwards, 2004). Their transport and channeling activities increase pore volume, water intake and flux through the profile, and moisture holding capacity. Faunal breakdown of coarse litter into finer particles exposes greater surface area to aeration, moisture and attack by decomposers (Paul and Clark, 1996). Specifically, earthworms stabilize soil organic matter fractions within their casts, and they also increase the mineralization of organic

11 matter in the short term by altering physical protection within aggregates and enhancing microbial activity (Bertrand et al., 2015)

2.5.2 Millipedes (Myriapoda: Diplopoda) Soil millipedes are saprophagous invertebrates which live in litter layers or in the upper few centimeters of the soil. The millipedes have multi-segmented bodies, in length vary from two millimeters to 300 mm. The most important diagnostic feature for millipedes is the occurrence of diplo-segments. Millipede bodies comprise a head, followed by four trunk segments and the posterior body, consisting of diplosegments, each of them carrying two pairs of legs. The trunk is formed by the legless collum segment, and three segments with one pair of legs each (Bueno- Villegas et al., 2008).

Most millipedes are saprophagous feeding on organic debris and humus (Paul and Clark, 1996). Soil invertebrate communities have been shown to vary according to various habitat factors including physico-chemical characteristics of the soil. Millipede abundance and biomass were positively correlated with rainfall, soil moisture, soil Ca content and soil temperature (Ashwini and Sridhar, 2006). Millipedes occur in a wide altitudinal range and constitute a major component of the soil-litter macrofauna.

Millipedes play an important role in the soil formation process (Bano, 1992). Dangerfield (1990) states that detritus feeders may process up to 30 % of the annual dead organic matter input to most soils and affect the decomposition of this material. Millipedes have been shown in other experiments to play an important role in the formation of humus, as they feed on and break down woody debris as well as decaying leaves (Ruan et al., 2005). Additionally, millipedes can be good indicator species to determine the degradation of habitats (Snyder and Hendrix, 2008)

2.5.3 Ants (Hymnoptera: Formicidae) Ants are present in most terrestrial ecosystems. There are approximately 11,832 known species of ants (Schuldt et al., 2011) and constitute half of the global insect biomass (Benckiser, 2010). Ants can be used as bio-indicators of environmental quality because they are sensitive to changes in environmental conditions, have high species richness and wide geographical distribution. Furthermore, establishment of nests is influenced by a variety of factors including land-use type, abiotic conditions and primary productivity (Gómez et al., 2003). Ants are eusocial insects

12 organized into colonies with two or more adult generations coexisting together and they are divided in reproductive and non-reproductive castes (Hölldobler and Wilson, 1990).

Soil and litter inhabiting ants are of great importance to nutrient cycling because of their saprophytic feeding and soil turning activity (Brühl et al., 1999). Ants act as soil tillers by changing the structure and chemical properties of the soil through construction of mounds (Folgarait, 1998). These mounds may have an increase of carbon, nitrogen and phosphorus resulting from the accumulation of plant and animal remains in their nests (Hölldobler and Wilson, 1990; Folgarait, 1998). Additionally ants fulfill other key roles such as maintenance of energy and material flow in soils, rearrangement of soil particles, favoring the movement of organic matter and more rapid decomposition of litter and organic residues (Wagner et al., 2004). Ants also contribute to improving soil aggregation and aeration by creating macropores and subterranean galleries constructed with a mixture of organic matter and mineral soil. The alterations of soil horizons and organic matter decomposition by ants modify soil chemical properties such cations, organic matter and pH (Lafleur et al., 2005; Frouz and Jilková, 2008) and enhance microbial activity (Dauber et al., 2001). Ants are also regarded as powerful monitoring tools in environmental management as response of ants to disturbance have been shown to reflect those of other ecosystem processes and biota (Hoffmann 2003; Philpott et al., 2010).

Ants are known to have trophobiotic relationships with insects of three orders: Hemiptera, including insects of three suborders: Sternorrhyncha (aphids, scale insects, mealybugs, and white flies), Auchenorrhyncha (leafhoppers, planthoppers) (Delabie, 2001) and Heteroptera (true bugs) (Waldkircher et al., 2004), Lepidoptera (larvae of Lycaenidae, Riodinidae and Tortricidae) (Pierce et al., 2002) and Hymenoptera (larvae of the sawfly). Many scale insects are tended by ants that consume their exudates as an important source of nutrition. In turn attendant ants increase the survival and population of scale insects by: directly protecting them from predators and parasites(Ness and Bronstein, 2004; Mgocheki and Addison, 2009); removing honeydew to prevent mold infestation; transporting the scale nymphs to suitable feeding sites on host plants; and building shelters to protect scale insects (Fischer et al., 2001). In a study of cassava fields in the coastal savanna and rain forest zones of Ghana, eight species of ants, mostly in the genera Camponotus, Crematogaster and Pheidole, were found attending cassava mealybug, Phenacoccus manihoti. Ant densities were positively correlated to mealybug population densities and they

13 reduced parasitism rates by the predators to half compared to the rates observed on mealybug colonies of equal size that were not attended (Mgocheki and Addison, 2009). Ants also benefit other insects that do not produce exudates by depressing populations of their natural enemies.

Although many studies have abundantly documented the detrimental impacts of ants on biological control (Martinez-Ferrer et al., 2003, Cudjoe et al., 2009). In some studies ants were found to prey on and suppress populations of the scale insects (Shanahan and Compton, 2000). The conservation and use of ants for biological control has been underestimated by pest managers for decades due to lack of understanding of the ecological role of ants in agro ecosystems and natural vegetation (Perfecto and Castineiras, 1998; Cudjoe et al., 2009).The trophobiotic relationship between ants and their adopted Hemiptera needs further investigation to understand aggression exhibited by ants towards natural enemies of their attended Hemiptera (Mgocheki and Addison, 2009).

2.6 Effect of cropping system on soil properties and coffee productivity Shade is hypothesized to bring the greatest benefits in productivity and quality for coffee plants which grow in suboptimal and heat-stressed growing regions, where shade can modify environmental conditions to favour growth of coffee (Jezeer and Verweij, 2015). Earlier, Vaast et al. (2006) reported that coffee grown under shade had significantly bigger beans and explained that it is likely that the lower temperature facilitates a longer maturation period allowing for increased berry filling. Similar positive effects of shade and altitude on bean size were reported earlier by Guyot et al. (1996). By increasing resilience to climatic variability and stabilizing productivity and income, shade trees can therefore improve farmers’ livelihoods (Jezeer and Verweij, 2015). Shade trees with 35 – 65 % shade cover have been found to influence the greatest yields (Perfecto et al., 2005).

Shaded coffee plantations promote a high abundance and diversity of natural enemies that help to regulate herbivores, weeds and disease pathogens. It also harbor a higher diversity of native pollinators which have been shown to contribute to higher coffee yields (Perfecto et al., 2007). The forest-like conditions of the coffee systems allow for a wealth of ecological dynamics to occur including increased bird habitat, natural pest control, making such systems vital for conservation initiatives (Rice, 2010).

The soil and vegetation have a complex interrelation because they develop together over a long period of time. Vegetation cover influences the chemical properties of soil to a great extent through the selective absorption of nutrient and their capacity to return them to the soil (Qasba et al., 2017) Similarly, less soil moisture evaporation under the canopy of trees lowers soil temperature resulting in less organic matter decomposition and consequently more organic carbon and total nitrogen accumulation (Jezeer and Verweij, 2015). A study in Nicaragua reported an increase by 19 % in soil fertility (expressed as cation exchange capacity) in shade-grown coffee farms (Rice 2010). Infiltration rate, which is important for soil moisture and plant growth in unshaded coffee systems decreased by as much as 75 % over a time span of 6 - 10 years. Soil moisture in sun coffee farms can be 42 % lower compared to coffee farms that have leafy foliage as canopy (Rice, 2010). With crops, such as coffee, agroforestry may improve soil structure and increase soil organic matter content and plant-available nutrients (Mendonça and Stott, 2003). The primary objective of agroforestry systems in highlands is to increase physical protection against soil erosion and improve soil fertility

2.7 Effect of altitude on soil properties and coffee productivity The irregular terrain and topography in the mountain areas lead to slope diversity and heterogeneity, which are significant factors for the intensity of soil erosion (Jiang and Pilesjö, 2014). This has implications for the productivity of plantations at different altitudes, and the potential benefits of shade trees. Several benefits of shading in coffee have been reported but if farmers at higher altitudes are to switch to a shaded system, the presumed decrease in coffee yield and quality should be compensated by a price premium (Jezeer and Verweij, 2015).

Altitude influences soil water balance, soil erosion, geologic deposition processes, species and biomass production of the native vegetation and cultivated plants (Tan et al, 2004) which in turn influence the nutrient status of mountain ecosystems (Walker et al., 2000). For example, nitrogen mineralization often differs with vegetation type, altitude, and topographic position, which are often due to variations in soil organic matter, temperature, and soil water availability (Von Lutzow and Kogel-KNabner, 2009). Early studies showed that the N mineralization or nitrification rates reduced with increasing altitude (Kitanyanma et al., 1998; Hart and Perry Dnge, 1999) and this is because of decrease in temperature (Zhang et al., 2011). Tusi et al. (2004) also explained that pH, available P, exchangeable cations like; Ca, Mg are significantly higher on the slope at 0-5 cm soil

CHAPTER THREE

Materials and Methods

3.1 Description of study sites The study was carried out in eastern Uganda on the north-eastern slopes of Mt. Elgon in the two district of Sironko and Kapchorwa. The study covered five sub-counties of Bugitimwa, Bukalasi in Sironko, and Chema, Kapteret, and Tegeres in Kapchorwa. The climate of the Mt. Elgon region can be defined as humid subtropical. The average minimum and maximum temperature is 15°C and 28°C respectively and mean annual temperature of about 23°C. The mean annual precipitation is generally around 1500 mm (Bamutaze et al., 2010). Generally, the soils in Mt. Elgon are deep and derived from volcanic ash as the product of a single weathering cycle (Jiang et al., 2014). The main soil parent materials in Mt. Elgon include volcanic ash and agglomerates, metamorphic rocks, and mixed volcanic-metamorphic rocks (Bamutaze, 2010).The land use types in the Mt. Elgon region are classified as crop lands, secondary forest, natural forest, bare land, and built-up areas (Jiang et al., 2014). Agriculture is the main economic activity with coffee being the main cash crop in the area. Coffee is often grown with shade trees and other crops mainly banana, maize, beans and potatoes. The predominant shade tree species include Markhamia lutea (Bignoniaceae), Grevillea robusta (Proteaceae), Milicia excelsa (Meliaceae), Albizia spp. (Fabaceae), Cordia millenii (Boraginaceae), Artocarpus heterophyllus (Moraceae), Mangifera indica (Anacardiaceae), Persea americana (Lauraceae), Carica papaya (Caricaceae), Psidium guajava (Myrtaceae), Syzygium cumini (Myrtaceae), Croton macrostachyus (Euphorbiaceae), Maesopsis eminii (Rhamnaceae), Ficus natalensis (Moraceae), Sesbania sesban (Fabaceae), Gliricidia spp. (Fabaceae), Acacia spp. (Fabaceae), Leucaena leucocephala (Fabaceae), Tephrosia vogelii (Fabaceae), Alnus spp. (Betulaceae), Calliandra spp.(Fabaceae), Inga spp. (Fabaceae) and Erythrina abyssinica (Fabaceae) (EcoTrust, 2012).

3.2 Study design The study was conducted in representative sites selected within the two districts in the Mt. Elgon region. The study sites were categorized by altitude into: i) low (1300-1499 m.a.s.l), ii) mid (1500- 1679 m.a.s.l) and iii) high (1680-2100 m.a.s.l) altitude. In the demarcated altitude belts, farmer fields were purposively selected based on land use management defined by coffee cropping

16 systems. The cropping system were categorized as: i) coffee monocrop, ii) coffee-annual crops (coffee intercropped with annuals such as beans, potatoes etc.), iii) coffee-banana, and iv) coffee- banana-shade trees. The cropping system aspect had three replicates per altitude belt making a total of 12 farm sites per altitude category per district leading to a total of 72 study sites. Already established coffee farms of about one acre were purposively selected for the study. A minimum distance of at least 1 km was considered between selected farms. The farming households were selected with the assistance of local Agricultural officers.

3.3 Data collection Longitudinal biological monitoring surveys were conducted at each selected site to achieve the study objectives. The study was done in two rounds. Data were collected capturing occurrence and abundance of the soil-based root mealybug, soil physical properties (moisture, and temperature), chemical properties (N, P, K, OM, pH, Na+, K+, Ca2+ and Mg2+), and biological properties (soil macrofauna: earthworms, millipedes, and ants); ambient microclimate (relative humidity and temperature) and coffee yield as detailed below.

3.3.1 Root mealybug This study focused on the soil inhabiting root mealybug as a pest of coffee. Ten trees were randomly selected in each farm site following methodologies of Magina (2007). Mealybug occurrence was estimated using a severity score of 1 - 5, where 1 = no plant symptoms and no infestation; 2 = no plant symptom but infestation present; 3 = mild stunting and infestation present; 4 = stunting, leaves beginning to yellow and infestation present; 5 = leaves yellow, wilting and infestation present. Incidence was confirmed by scrapping off a small amount of soil around the collar to expose the whitish infestation mass following the procedures of Karungi et al. (2015) Severe root mealybug damage manifests as yellowing and wilting of foliage, which falls off gradually (Rutherford and Phiri, 2006).

3.3.2 Soil properties and microclimate This section include sampling for soil macrofauna and obtaining soil samples for laboratory analysis.

Macrofauna abundance Pit fall traps were used for ants. Ten pit fall traps in each study field were established in a zig zag pattern at 10 m apart, these were used to monitor ants on monthly basis for a period of 12 months. Polyethylene beakers of 500 ml filled with approximately 170 ml of 65% ethanol solution was used to preserve the trapped ants. Rain covers were placed approximately 10 cm above each trap to prevent flooding by rain following the guidelines of Dauber et al. (2005) and Haddad et al. (2011). On each sampling day, samples were collected from the traps and transferred to the laboratory for counting and categorisation. The occurrence of ants was recorded as counts per trap per site.

The earthworms and millipedes were determined from three randomly cast quadrats (1 m2) per field and the soils in the quadrat was dug out up to a depth of 15 cm. Earthworms and millipedes were then hand sorted from within the soil contained in a quadrat and preserved in 65 % ethanol for counting in the laboratory.

Ambient and soil microclimate Soil properties of temperature, and moisture (volumetric water content) at depth of 0 – 15 cm were determined in-situ using Procheck sensors (GS3 ruggedized soil moisture, temperature, & electrical conductivity sensor – Decagon devices). Ambient temperature and relative humidity were measured. Temperature and relative humidity were measured using a thermo-hygrometer pen (model 3402) following the techniques of Van Long et al. (2015). The microclimate readings were measured at three different positions in the field between 11:00 and 12:00 h as recommended by Bellow and Nair (2003).

Soil physical and chemical properties Composite soil samples obtained from 10 sub samples were obtained at a depth of 0 - 15 cm and 15 - 30 cm from each study site. The composite samples were air dried, sieved using a 2 mm sieve and then analyzed for soil organic matter (Wakley and Black method), texture (hydrometer method procedure of Bouyoucos), available phosphorus was extracted in Brady I solution and measured on colorimeter after colour complexing with ascorbic acid. Total nitrogen (Kjeldehal method) was determined after total digestion of the soil samples with a Silicic acid digestion mixture at 350 o C for 3 hours. Exchangeable bases of Na+, K+, Ca2+ and Mg2+ were extracted in neutral ammonium acetate as described in Okalebo et al. (2002) and measured on Atomic 18

Absorption Spectrophotometer. A checklist was also used to collect soil management practices (type of input/amendment if any) information from the host farmers. They were categorised as 1= organic-intensive, 2= inorganic-intensive, and 3= no management.

3.3.3 Coffee yield Data were collected on number of fruiting nodes, and number of berries per branch of randomly selected ten coffee plants on each study site. Number of fruiting nodes and berries counted per branch were taken from three randomly selected branches; one each at the top, middle and bottom of the coffee plant following guidelines of Van Long et al. (2015).

3.4 Data analysis Analysis of variance (ANOVA) was used to evaluate the influence of cropping system and altitude on soil physical chemical properties, and microclimate variables. Data on mealybug severity were transformed to achieve homogeneity of variance, using square root transformation (X+0.5)1/2. Data on soil fauna was log transformed before subjected to ANOVA because it was not normally distributed and soil management practices were added as covariates. Means which were significant were separated using Fischer’s protected LSD at 5 %. Genestat 16th edition statistical package was used in the analysis

CHAPTER FOUR

Results

4.1 Effect of cropping system and altitude on root mealybug severity Results showed that cropping system (P < 0.001), altitude (P < 0.001) and their interaction (P < 0.05) significantly influenced infestation of the root mealy bug on coffee. Root mealybug severity significantly reduced under the coffee-banana, and coffee-banana- trees system irrespective of the altitude. The coffee monocrop system at low altitude realized most of the mealybug severity. It was noted that severity of root mealybug was generally highest at the low altitude (1300 -1499 m.a.s.l) (Figure 1)

3.5

5) - 3

2.5 Low Altitude Mid Altitude 2 High Altitude 1.5

Root mealybug severity (1 severity mealybug Root 0.5 Coffee-banana-trees Coffee-banana Coffee monocrop Coffee-annuals

Cropping systems

Figure 1: Effect of cropping system and altitude on coffee root mealybug severity (Scale of 1-5, where 1 = no plant symptoms and no infestation; 2 = no plant symptoms but infestation present and 5 = leaves yellow, wilting and infestation present). Error bars—standard error of the mean)

4.2 Effect of cropping system and altitude on soil properties and microclimate

4.2.1 Abundance of earthworms Cropping system had a very high significant effect on the population of earthworms (P < 0.001) as well as interaction of cropping systems and altitude (P < 0.001). There was a high number of earthworms in the coffee-banana-shade tree systems at all altitudes (Figure 2) although the coffee- banana systems realized significantly more earthworm (4 m-2) at the mid altitude. The earthworm population decreased in the coffee monocrop and reduced further when coffee was intercropped

20 with annual crop at all altitudes. Therefore, the lowest number of earthworms was registered in the coffee-annual crop systems (Figure 2).

4 2 3.5

2.5 Low Altitude 2 Mid Altitude 1.5 High Altitude

1 No. of earthworms / m / earthwormsof No. 0.5 Coffee-banana-trees coffee-banana coffee monocrop coffee annual crop Cropping systems

Figure 2 : Effect of cropping system at different altitudes on number of earthworms

4.2.2 Abundance of millipedes Altitude significantly influenced millipede abundance (P < 0.001). Mid altitude farms had the most number of millipedes (Figure 3). Cropping system weakly influenced number of millipede (P < 0.05) and the interaction of cropping system and altitude had no significant effect on abundance of millipedes (P > 0.05). The coffee-banana- trees system had the highest number of millipedes though it did not differ significantly from the coffee-banana systems. The lowest number of millipedes was in the coffee-monocrop systems (Figure 4)

0.6

2 0.5

0.4

0.3

0.2

0.1

No. of millipedes millipedes m / of No. 0 Low altitude Mid altitude High altitude

Altitudinal gradients

Figure 3: Effect of altitude on number of millipedes

0.45

0.4 2 0.35

0.3

0.25

0.2

0.15

0.1 No. of millipedes millipedes m / of No. 0.05 Coffee-banana-trees coffee-banana coffee monocrop coffee-annuals

Cropping systems

Figure 4: Effect of cropping system on number of millipedes

4.2.3 Abundance of ants Altitude (P <0.01) and cropping system (P < 0.001) significantly affected population of ants in the different coffee farm sites, although their interaction had no significant effect. Trends in the results show that ant numbers decreased with increased cropping diversity. The least number of ants was observed in the coffee-banana systems, which was not significantly different from the coffee- banana-tree systems. The coffee-annuals systems had relatively higher number of ants though there was no significant difference from the coffee-monocrop systems (Figure 5). The number of ants increased with altitude, with the high altitude farms having the highest number of ants (Figure 6).

11 10 9 8 7 6 5 4

Number antstrap / of Number 3 2 Coffee-banana-trees Coffee-banana Coffee monocrop Coffee-annuals Cropping systems

Figure 5: Effect of cropping system on number of ants

9 8 7 6 5 4

3 Number antstrap / of Number 2 Low altitude Mid altitude High altitude Altitudinal gradients

Figure 6: Effect of altitude on number of ants

4.2.4 Effect on soil moisture and temperature Cropping system, altitude and their interaction significantly influenced content of soil moisture (P < 0.001). The diverse coffee-banana-shade tree mixture had more moisture content followed by coffee monocrop system. The coffee-banana-shade trees systems at the high altitude had high moisture levels of about 0.45 m3/m3. The coffee-annual crop systems had the least moisture content which further reduced at lower altitudes (Figure 7). Farms at high altitude had more moisture content in the soil compared to the mid and lowland farms. The lower altitude farms registered the lowest moisture levels but did not differ significantly from the mid altitude (Figure 7).

0.47

0.45 Low altitude 0.43 Mid altitude 0.41 High altitude 0.39

0.37

0.35 Soil moisture (m³/m³) moisture Soil

0.33 Coffee-banana-trees Coffee-banana Coffee monocrop Coffee-annuals

Cropping systems

Figure 7: Effect of cropping system at different altitudes on soil moisture

Cropping system significantly (P < 0.001) affected soil temperature. The highest soil temperature was recorded in the coffee-annuals, which was not significantly different from the coffee monocrop (Figure 8). Soil temperatures under coffee plantation significantly dropped with inclusion of banana and trees. The least soil temperature was recorded in the coffee-banana-tree systems and it did not differ significantly (P > 0.05) from the coffee-banana system. Altitude had a strongly significant (P < 0.001) effect on soil temperature with the highest temperature recorded in the mid altitude followed by the low altitude and the lowest temperature recorded in the high altitude farms (Figure 8). 27

C) 0 Low altitude 25 Mid altitude 24 High altitude 23

temperature ( temperature 22

Soil 21 Coffee-banana-trees Coffee-banana Coffee monocrop Coffee-annuals

Cropping systems

Figure 8: Effect of cropping system at different altitudes on soil temperature

4.2.5 Effect on soil chemical properties Cropping system (P < 0.05) and altitude (P < 0.001) significantly influenced the soil organic matter in the different farm sites at the soil depth of 0 - 15 cm. However, there were no significant differences between cropping systems, and altitude at soil depth of 15 - 30 cm. For the top soil (0 - 15 cm), the coffee-banana-tree systems had the highest amount of organic matter and the least amounts were registered in the coffee-annual crop systems (Figure 9). The mid altitude farms registered the highest amount of organic matter and the lowest amounts were registered in the high altitudes (Figure 10). Incidentally, annuals intercrop and high altitude farms fell below the critical organic matter values (3 %)

5.5

4.5

3.5

3 Soil organic matter (%) matter organic Soil 2.5 Coffee-banana-trees coffee-banana coffee monocrop coffee-annuals Cropping systems

Figure 9: Effect of cropping system on soil organic matter at soil sampling of 0 - 15cm

5.5 5 4.5 4 3.5 3 2.5 2

Soil organic matter (%) matter organic Soil 1.5 Low Altitude Mid Altitude High Altitude Altitudinal gradients

Figure 10: Effect of altitude on soil organic matter

Cropping system (P < 0.05) and altitude (P < 0.001) significantly influenced total nitrogen in the top soil (0-15 cm) but there were no significant differences in the sub soil (15-30 cm). Most of the total nitrogen was observed in the coffee-banana-trees systems (0.28 %) and the lowest registered in the coffee-annual crop systems (0.21 %) (Figure 11). The farms in the mid altitude had higher total nitrogen (0.30 %) compared to the farms in the low (0.24 %) and high altitude (0.19 %) (Figure 12). There was a positive correlation between soil organic matter and total nitrogen (Figure 13).

0.31 0.29 0.27 0.25 0.23 0.21 0.19

Total nitrogen (%) nitrogen Total 0.17 0.15 Coffee-banana-trees coffee-banana coffee monocrop coffee-annuals Cropping systems

Figure 11: Effect of cropping system on total nitrogen at soil sampling depth of 0 - 15cm

0.35

0.3

0.25

0.2

0.15 Total nitrogen (%) nitrogen Total

0.1 Low Altitude Mid Altitude High Altitude

Altitudinal gradients

Figure 122: Effect of altitude on total nitrogen at soil sampling depth of 0 - 15cm

0.6 0.5 Y = 0.0594X + 0.0146

0.4 R² = 0.88 0.3 0.2

0.1 Total nitrogen (%) nitrogen Total 0 0 1 2 3 4 5 6 7 8 9 Soil organic matter (%)

Figure 133: Correlation between soil organic matter and total nitrogen

There was no significant effect on pH, available phosphorus, potassium, exchangeable bases. Soils under coffee-intercrops cropping systems had pH between 7.13 and 7.17 in the top soil. The lowest soil pH value of 6.46 was observed from soils obtained in the coffee-annuals at high altitude. It should be noted that the observed pH ranges are acceptable for plant growth. There were high concentrations of K, Ca, Mg and Na both in the top soil (Table 2) and sub soil samples (Table 3).

Table 1: Soil pH, available P (ppm), K, Na, Ca, and Mg (cmol+ kg-1) under cropping system at different altitudes (0 -15cm soil depth)

Cropping Low altitude Mid altitude High altitude System pH P K Ca Mg Na pH P K Ca Mg Na pH P K Ca Mg Na Coffee- Banana-Trees 7.17 90 5.24 9.3 2.70 1.12 6.81 116 4.50 8.1 2.22 0.84 6.64 114 5.53 8.4 2.42 0.76 Coffee- Banana 7.13 60 4.68 9.2 2.81 1.26 6.94 79 3.31 10.6 2.84 1.05 6.77 136 5.66 9.5 2.53 0.57 Coffee monocrop 6.47 195 5.48 11.3 3.18 0.56 7.00 138 5.40 6.8 1.90 1.05 7.11 27 2.61 9.0 2.80 1.14 Coffee-annual crops 6.93 24 2.74 5.1 1.58 0.95 6.80 89 2.73 9.1 2.65 0.71 6.46 70 3.26 8.2 2.42 0.91 P-value 0.74 0.11 0.41 0.37 0.25 0.91 0.89 0.71 0.23 0.74 0.75 0.93 0.52 0.37 0.42 0.98 0.99 0.91

Table 2: Soil pH, available P (ppm), K, Ca, Mg and Na (cmol+ kg-1) under cropping system at different altitudes (15 - 30 cm soil depth)

Cropping Low altitude Mid altitude High altitude System pH P K Ca Mg Na pH P K Ca Mg Na pH P K Ca Mg Na Coffee- Banana- Trees 7.19 105 4.98 8.1 2.38 1.18 6.75 77 3.67 7.36 1.85 0.78 6.7 153 5.87 9.9 2.87 0.64 Coffee- Banana 6.82 20 1.86 7.7 2.10 1.10 6.66 101 3.77 5.73 1.60 0.85 6.7 127 3.43 7.0 1.50 0.57 Coffee monocrop 6.57 90 4.21 10.1 2.81 0.59 6.92 106 3.11 5.99 1.62 0.91 6.7 26 2.80 5.7 2.09 1.18 Coffee- annual crops 6.53 19 2.12 6.0 1.96 0.58 6.68 92 1.93 7.57 2.21 0.49 6.5 62 2.23 5.6 1.68 0.57 P-value 0.29 0.06 0.08 0.61 0.72 0.66 0.85 0.96 0.60 0.83 0.77 0.86 0.78 0.06 0.08 0.52 0.27 0.88

4.2.6 Effect of cropping system and altitude on microclimate Cropping system (P < 0.01) and altitude (P < 0.001) significantly influenced the ambient temperature in the coffee plantations. The coffee-banana cropping systems registered lower ambient temperatures and temperatures further dropped up to 23.1 0c in systems where trees were added. Higher temperatures were recorded in the coffee monocrop systems but were not significantly different from the coffee-annual systems (Figure 14). The lowest ambient temperatures were recorded in the high altitude farms with temperatures dropping up to 22.6 0c and the highest temperatures were recorded in the lower altitude farms though these did not differ significantly from the mid altitude farms (Figure 15). 25.5 25 24.5

C) o ( 23.5 23

22.5 Ambient temperature temperature Ambient 22 Coffee-banana-tree coffee-banana Coffee monocrop Coffee-Annual Cropping systems

Figure 14: Effect of cropping system on ambient temperature

25.5 C) o 25 24.5 24 23.5 23 22.5 22 21.5 21

Ambient temprature ( temprature Ambient 20.5 Low altitude Mid altitude High altitude Altitudinal gradient

Figure 15: Effect of altitude on ambient air temperature in coffee plantations

It was only altitude that significantly (P < 0.001) changed the relative humidity in the different cropping systems. The mid altitude farms had the lowest relative humidity (64 %) and the highest relative humidity was recorded in the high altitude farms (68.7 %) though it did not differ significantly (P > 0.05) from the low altitude farms (Figure 16).

72 70 68 66 64 62

60 Relative (%) Humidity Relative 58 Low Altitude Mid Altitude High Altitude Altitudinal gradients

Figure 16: Effect of altitude on relative humidity in coffee plantations of Mt. Elgon

4.3 Effect of coffee cropping system and altitude on coffee yield indicators

4.3.1 Effect on number of fruiting nodes per branch Cropping system, altitude and their interaction significantly affected the number of fruiting nodes (P < 0.001). The coffee-banana-tree cropping systems had the highest number of fruiting nodes though it did not differ significantly (P > 0.05) from the coffee-banana system. The lowest number of fruiting nodes was registered in the coffee-annual systems but it did not differ significantly from the coffee monocrop system. The coffee monocrop and coffee annuals systems at high altitude had branches with more fruiting nodes than in the mid and low altitudes (Figure 17).

9 8.5 8 7.5 7 Low Altitude 6.5 Mid Altitude 6 High Altitude 5.5 5 4.5 No. of fruiting nodes / branch / nodes fruitingof No. 4 Coffee-banana-trees coffee-banana coffee monocrop coffee-annual crop

Cropping systems

Figure 17: Effect of cropping system at different altitudes on number of fruiting nodes per branch

4.3.2 Effect on number of berries per branch The number of berries per branch varied significantly (P < 0.001) in the different cropping systems, altitude gradients and their interaction. There were more berries per branch in the coffee-banana- tree cropping systems compared to the rest while the coffee monocrop systems had the lowest number of berries per branch but it did not differ significantly (P < 0.05) from the coffee-annual systems (Figure 18). The highest number of berries was registered in the coffee-banana-tree systems at the mid altitude and the lowest number of berries per branch was recorded in the coffee- annual systems in the mid altitude.

60 55 50 45 40 Low altitude 35 Mid altitude 30 High altitude 25

No. of berries branch / berries of No. 20 Coffee-banana-trees coffee-banana coffee monocrop coffee-annual crop Cropping systems

Figure 18: Effect of cropping system at different altitudes on the number of berries per branch

CHAPTER FIVE

Discussion

5.1 Effect of cropping system and altitude on the root mealybug It was noted that shaded systems reduced root mealybug severity compared to the unshaded systems. The significant reductions in the shaded systems can be attributed to alteration in microclimate leading to cooler habitats, increased moisture levels and better nutrient levels as shown in this study. Primarily, these favor vigorous growth and offers better resilience to environmental stresses as arabica coffee is favored by cool conditions (COMPETE, 2002). Furthermore, these conditions do not favor the coffee root mealybug whose damage is more apparent on nutrient-deficient soils, and are reported to multiply rapidly in dry weather (Rutherford and Phiri, 2006). The higher severity in the coffee monocrop and the coffee-annuals systems where some of the coffee plants had severe yellowing, others wilting and general stunting can therefore be explained by the warmer microclimate. This may further explain the higher severity of the root mealybug in the lower altitudes which are relatively warmer than the higher altitudes. It is therefore not surprising that the least severity was reported in the coffee-banana-trees systems at the high altitude. The fact that microclimate plays an important role in mealybugs dynamics was reported by Kasongo et al. (2011), Muwanika (2014) and Kabi et al. (2016). Indeed Kabi et al (2016), showed that intercropping pineapple with banana reduced infestation of the pineapple mealy bug. Shade trees are likewise reported to harbor a range of predatory birds and natural enemies of pests consequently contributing to biological control of pests (Alemu, 2015). This therefore may explain the further reducing effect of adding shade trees in coffee systems on root mealybug severity.

5.2 Effect cropping system and altitude on soil properties and microclimate

5.2.1 Effect cropping system and altitude on earthworms The results showed that the population of earthworms was more in the shaded coffee systems at low to medium altitudes. The coffee-banana-tree systems and coffee-banana system were characterized by relatively high soil organic matter that may have been brought about by additional litter from trees and banana, the higher soil moisture and the buffering of soil temperature levels. These conditions have been reported to favor survival and growth of earthworms (Riley et al., 2008; Hong et al., 2017). Further still, these systems are highly shaded and this discourages growth of weeds hence there is minimum tillage practiced, enabling undisturbed ecosystem for soil biota.

On the contrary, there is frequent tillage in the coffee-annual systems resulting from regular cultivation and weeding of the annual crops grown in the coffee. Tillage disturbs the habitat of soil biota, increases predation, and reduces organic matter, which the soil biota feed on and consequently reduce their population (Crittenden et al., 2014). It is indeed documented that intensive tillage reduces earthworm abundances and biomasses, and modifies species diversity and composition (Van Capelle et al., 2012; Pelosi et al., 2013; Ricci et al., 2015). The study showed that earthworms were more abundant in lower altitudes. This finding is in agreement with reports of Rozen et al. (2013), that the density and biomass of earthworms is negatively correlated with elevation. Relatedly, Kanchilakshmi and Thaddeus (2016), reported more earthworm abundance in low lying plains compared to high elevation areas.

5.2.2 Effect cropping system and altitude on millipedes Millipedes were more abundant at mid altitudes and in the coffee-banana-trees systems. Mid altitude and the coffee-banana-trees systems corresponded to high levels of soil organic matter and total nitrogen. These findings concur with the reports of Loranger-Merciris et al. (2008), who showed that millipedes prefer nitrogen-rich litter. The high soil nitrogen content may have resulted in higher nitrogen content of the leaves that fall to the ground favoring a higher occurrence of millipedes.

5.2.3 Effect cropping system and altitude on ants It was noted that the abundance of ants increased with elevation. Similar results were reported by Fleishman et al. (2000); Sanders (2002); Sanders et al. (2003); MontBlanc et al. (2007), Burwell and Nakamura (2011) and Orabi et al. (2011). The explanation may lie in the temperature ranges like in this study where high elevations had the lowest ambient temperature and highest ants’ abundance. Ants were higher in the coffee monocrop and coffee-annual systems. An explanation for this could be in the fact that these systems had high mealybug infestations. Some evidence shows majority of ants are exudate feeders obtaining most of their energy from homopterans (Davidson et al., 2003). Davidson et al. (2003), found that this was especially so for Camponotus species, one of the predominant genus found in this study. Other studies have also concluded that ant–homopteran associations constitute a major force regulating trophic structure and ant distributions (Blüthgen et al., 2000; Dejean et al., 2000). The root mealybug excrete honey dew, which ants consume as an important source of nutrition (Mgocheki and Addison, 2009).

5.2.4 Effect cropping system and altitude on soil organic matter and total nitrogen The concentration of soil organic matter and total nitrogen significantly varied similarly and had a very strong positive correlation. The positive relationship indicates that most of the nitrogen in the Mt. Elgon soil ecosystem is derived from soil organic matter. Their content was highest at mid altitudes. In general, organic matter content is expected to increase along elevation, since larger mineralization rates can be expected at higher temperatures and thus lower elevations (Bauw et al., 2016). As such the results of the organic matter and nitrogen content are not in line with the temperature profiles of the different altitudes. This is unexpected and may imply that other factors, not included in this study and probably related to farmer’s management are at play. The coffee- banana-tree systems, which had the highest amount of organic matter and nitrogen is characterized by more biomass production from leaves and branches of coffee, banana, and trees grown in the systems. Hence, they are characterized by high litter, which later decompose and contribute to the relatively higher amounts organic matter and nitrogen in these systems (Pender et al., 2009; Diaz et al., 2012). More still, the microclimate which is cool with higher moisture levels lowers the level of decomposition of organic matter and N mineralization.

5.2.5 Effect cropping system and altitude on soil temperature and moisture Soil moisture storage in the soil is a result of conservation practice and soil temperature. The systems that were shaded by banana and trees had lower ambient temperature within the system; which in turn lowers the soil temperature and conserves moisture due to reduced evaporation. Earlier studies (Möller and Assouline, 2007 and Pezzopane et al., 2011), reported that shading reduced mean global radiation (by 26 – 48 %), moisture loss and maximum ambient and soil temperature. More still, due to their deep rooting system, shade trees help in the deep infiltration of rain water, which in turn will contribute for the recharging of ground water. Shade trees likewise reduce evaporation from the land surface and evapotranspiration from plants (Alemu, 2015). Therefore the interaction of a shaded system and high altitude explains the lowest soil temperature and highest moisture readings in the coffee-banana-tree systems in the high altitude areas. Morais et al. (2006) explained that the reductions in soil temperature observed under shaded systems can mainly be attributed to ability of shaded soil to stabilize the local thermal balances and also to reduce the heat flux caused by the accumulated plant based biomass. More still, shading reduces and stabilizes the soil temperature by reducing the radiant flux reaching the soil and modifying the

34 temperature amplitude at the soil surface (Siebert, 2002). The high altitude had relatively low soil temperature

5.2.6 Effect cropping system and altitude on ambient air temperature and relative humidity Results of this study were in agreement with earlier studies by Lin (2007); Bote and Struik (2010); Siles et al. (2010); Ehrenbergerová et al. (2017) where ambient air temperature reduced in shaded systems compared to the unshaded systems. Trees reduce the amount of heat reaching the coffee plants during the day time (Alemu, 2015). Therefore, inclusion of shade trees and bananas into coffee systems lowers the ambient air temperature as seen in the results. It is important to note that the optimum mean annual temperature range for arabica coffee is 18 – 21 ºC and temperatures above 23 ºC result in acceleration of development and ripening of berries leading to loss of quality. Temperatures as high as 30 ºC may result in depressed growth but also in abnormalities such as yellowing of leaves and growth of tumors at the base of the stem (DaMatta and Ramalho, 2006). The results show that temperatures within the coffee fields were beyond that of optimal coffee growth (21 °C) but not beyond maximum limit of 30 ºC, the coffee-banana-shade trees was close to the optimum. The higher humidity at the high altitude farms may be explained by higher output of water vapor in these areas coupled with low temperatures and higher transpiration rate. Coffee plants require relative humidity of 70 – 85 % for optimum growth (USDA, 2012), however results show that the high altitude with the highest relative humidity was below the optimum. This indicates that areas suitable for optimal arabica coffee production is dwindling and production areas may be pushed to higher altitudes which are cooler.

5.3 Effect of cropping system and altitude on coffee yield indicators Crop yield is as a result of a number of factors, the results shown in the study may be explained by influence of cropping systems and altitude on pest regulation, soil properties and microclimate. The coffee-banana-tree cropping system which has not been significantly different from the coffee-banana systems has performed relatively well in terms of low pest severity, better soil physical, chemical and biological properties. It is therefore not a surprise that this systems showed better yield in terms of number of fruiting internodes and number of berries per branch. The coffee- banana-tree systems and the coffee-banana systems may have had longer branches explaining the higher number of fruiting nodes. Indeed coffee with 35 – 65 % shade cover have been found to give the greatest yields (Perfecto et al., 2005). The incorporation of biomass from coffee, banana,

35 and trees could have released nutrients to soils, improved physical environment of soil and enhanced crop uptake and thereby increased yields. Shaded coffee plantations promote a high abundance and diversity of natural enemies that help to regulate herbivores, weeds and diseases and also harbor a higher diversity of native pollinators which have been shown to contribute to higher coffee yields (Perfecto et al., 2007). The coffee-annual and coffee monocrop systems which were characterized by low vegetative growth, had shorter branches and hence fewer number of fruiting nodes and berries per branch. The non-shaded systems at high altitude had more number of fruiting nodes and berries and this may be explained by the relatively cooler temperatures in the higher altitude since arabica coffee grows optimally at low temperatures.

CHAPTER SIX

Conclusions and Recommendations

6.1 Conclusion The coffee-banana-shade trees systems performed better than the other systems across the different altitudinal ranges in terms of low pest occurrence, increased abundance of macrofauna (less ants), as well as in the microclimatic and soil properties studied. Noteworthy, results of the coffee- banana-trees were not significantly different from those of coffee-banana systems. On the contrary, the coffee-annual system generally gave the least performance in terms of the studied parameters, below the coffee mono-crop. Though it was hypothesized that shaded systems would give better yield performances at lower altitude, results of this study showed otherwise. The results indicate that arabica coffee should be grown with shade trees or banana in all altitudinal ranges studied to achieve the best yields. If coffee is to be grown as a sole crop, then it should be grown at altitudes higher altitudes.

Shaded coffee intercrops had enriched soil biota represented by high population of earthworm, and millipedes. Furthermore, there was higher concentrations of soil organic matter and total nitrogen, as well high moisture content and low soil temperature in the shaded systems. These indicators showed that the shaded coffee intercrops is more sustainable, which is an important factor in highland farmlands in the Mt. Elgon region.

6.2 Recommendations From the results of this study, I recommend: i. Inclusion of banana and trees in the coffee systems at all altitudes in the Mt. Elgon region for improved productivity and buffering of microclimate. Farmers, however may continue applying organic fertilizer in these systems for sustainable soil management. ii. Growing coffee with annual crops is detrimental due to frequent tillage practices involved in growing of annual crops; minimum tillage practices should be used when annual crops are being added to the system. iii. Further studies to establish the diversity of earthworms, ants and millipedes; evaluate the different cropping systems for coffee disease management in the farmlands in the Mt. Elgon region

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APPENDIX

Appendix 1: Soil organic matter as influence by cropping systems at different altitudes in Mt. Elgon region of eastern Uganda (interactions) Soil sampling depth 0-15 cm (%OM) 15-30 cm (%OM) Altitude Altitude Cropping system Low Mid High Low Mid High 1 4.97 5.33 3.26 3.32 3.73 2.97 2 3.16 4.88 3.67 3.22 4.37 2.68 3 2.90 5.05 3.30 2.99 4.10 4.11 4 3.51 4.33 2.02 2.11 3.53 2.32 p-value 0.04 0.69 0.12 0.13 0.77 0.53 Where 1= Coffee-banana-trees, 2= Coffee-banana, 3= Coffee monocrop, 4= Coffee-annuals

Appendix 2: Percentage Nitrogen as influenced by cropping systems at different altitudes in Mt. Elgon region of eastern Uganda (interactions)

Soil sampling depth 0-15 cm (%N) 15-30 cm (%N) Altitude Altitude Cropping system Low Mid High Low Mid High 1 0.33 0.31 0.20 0.22 0.23 0.19 2 0.23 0.29 0.22 0.21 0.25 0.17 3 0.16 0.32 0.24 0.19 0.25 0.26 4 0.23 0.26 0.14 0.17 0.22 0.16 p-value 0.11 0.69 0.22 0.50 0.89 0.65 Where 1= Coffee-banana-trees, 2= Coffee-banana, 3= Coffee monocrop, 4= Coffee-annual crop

Appendix 3: Analysis of variance tables for soil fauna Analysis of variance for mealybug severity (1_5)

Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 19.96087 6.65362 86.46 <.001 Elevation 2 1.95677 0.97838 12.71 <.001 Cropping System. Elevation 6 1.10631 0.18438 2.40 0.027 Residual 708 54.48246 0.07695 Total 719 77.50639

Analysis of variance for number of earthworms Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 16.6975 5.5658 8.61 <.001 Elevation 2 1.1950 0.5975 0.92 0.001 Cropping System .Elevation 6 15.7600 2.6267 4.06 <.001 Residual 420 271.6087 0.6467 Total 431 305.2612

Analysis of variance for number of millipedes Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 0.9277 0.3092 2.95 0.032 Elevation 2 2.3655 1.1827 11.29 <.001 Cropping System .Elevation 6 1.0127 0.1688 1.61 0.142 Residual 420 44.0056 0.1048 Total 431 48.3115

Analysis of variance for number of ants Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 46.611 15.537 12.64 <.001 Elevation 2 14.174 7.087 5.76 0.004 Cropping System .Elevation 6 5.912 0.985 0.80 0.570 Residual 276 339.388 1.230 Total 287 406.085

Appendix 4: Analysis of variance tables for microclimate Analysis of variance for Soil Moisture Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 0.205183 0.068394 13.18 <.001 Elevation 2 0.201737 0.100868 19.44 <.001 Cropping System .Elevation 6 0.129054 0.021509 4.14 <.001 Residual 708 3.674394 0.005190 Total 719 4.210368

Analysis of variance for Soil Temperature Source of variation d.f. s.s. m.s. v.r. F pr. Cropping System 3 170.548 56.849 12.59 <.001 Elevation 2 683.929 341.965 75.76 <.001 Cropping System. Elevation 6 68.922 11.487 2.54 0.019 Residual 708 3195.793 4.514 Total 719 4119.192

Analysis of variance of Ambient Temperature

Source of variation d.f. s.s. m.s. v.r. F pr. Cropping system 3 65.535 21.845 3.97 0.009 Elevation 2 205.977 102.988 18.72 <.001 Cropping system. Elevation 6 34.940 5.823 1.06 0.389 Residual 204 1122.158 5.501 Total 215 1428.610

Analysis of variance for Relative humidity

Source of variation d.f. s.s. m.s. v.r. F pr. Cropping system 3 399.82 133.27 1.95 0.123 Elevation 2 950.35 475.17 6.96 0.001 Cropping system .Elevation 6 348.29 58.05 0.85 0.533 Residual 204 13932.48 68.30 Total 215 15630.94

Appendix 5: Analysis of variance for coffee yield Analysis of variance (adjusted for covariates) for Number of Fruiting Internodes Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 1712.37 570.79 34.75 0.77 <.001 Elevation 2 896.96 448.48 27.31 0.95 <.001 Cropping System .Elevation 6 1121.99 187.00 11.39 0.97 <.001 Covariates 2 135.44 67.72 4.12 0.016 Soil management practices 2 135.44 67.72 4.12 0.016 Residual 2146 35246.06 16.42 1.00 Total 2159 39323.90

Analysis of variance (adjusted for covariates) for number of coffee berries per branch Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Elevation 2 9956.5 4978.2 8.40 0.94 <.001 Cropping System. Elevation 6 18998.7 3166.5 5.35 0.96 <.001

Covariates 2 1320.8 660.4 1.11 0.329 Soil management practices 2 1320.8 660.4 1.11 0.329 Residual 706 418240.5 592.4 1.00 Total 719 483811.9

Appendix 6 : ANOVA tables for soil nutrients at soil depth of 0 - 15cm

Analysis of variance (adjusted for covariates) for % Ca (Cmolskg-1 )

Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 55.38 18.46 0.60 0.73 0.615 Elevation 2 0.70 0.35 0.01 0.94 0.989 Cropping System. Elevation 6 32.15 5.36 0.18 0.96 0.982 Covariates 2 30.33 15.17 0.50 0.611 Soil management practices 2 30.33 15.17 0.50 0.611 Residual 58 1772.13 30.55 0.98 Total 71 1903.78

Analysis of variance (adjusted for covariates) for % p (ppm)

Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 28264. 9421. 1.43 0.73 0.242 Elevation 2 3599. 1799. 0.27 0.94 0.762 Cropping System. Elevation 6 26076. 4346. 0.66 0.96 0.681 Covariates 2 8608. 4304. 0.65 0.523 Soil management practices 2 8608. 4304. 0.65 0.523 Residual 58 381308. 6574. 0.99 Total 71 443779.

Analysis of variance (adjusted for covariates) for K (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 46.494 15.498 2.40 0.73 0.077 Elevation 2 4.508 2.254 0.35 0.94 0.707 Cropping System. Elevation 6 23.484 3.914 0.61 0.96 0.725 Covariates 2 2.080 1.040 0.16 0.852 Soil management practices 2 2.080 1.040 0.16 0.852 Residual 58 374.790 6.462 0.97 Total 71 450.124

Analysis of variance (adjusted for covariates) for Mg (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 3.160 1.053 0.53 0.73 0.664 Elevation 2 0.150 0.075 0.04 0.94 0.963 Cropping System. Elevation 6 3.773 0.629 0.32 0.96 0.926

Covariates 2 0.953 0.476 0.24 0.788 Soil management practices 2 0.953 0.476 0.24 0.788 Residual 58 115.436 1.990 0.97 Total 71 124.373

Analysis of variance (adjusted for covariates) for N_%

Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 0.058594 0.019531 2.78 0.73 0.049 Elevation 2 0.109445 0.054722 7.78 0.94 0.001 Cropping System. Elevation 6 0.048510 0.008085 1.15 0.96 0.346 Covariates 2 0.009804 0.004902 0.70 0.502 Soil management practices 2 0.009804 0.004902 0.70 0.502 Residual 58 0.407796 0.007031 0.99 Total 71 0.636350

Analysis of variance (adjusted for covariates) for Na (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 0.158 0.053 0.05 0.73 0.986 Elevation 2 0.377 0.188 0.17 0.94 0.846 Cropping System. Elevation 6 0.851 0.142 0.13 0.96 0.993 Covariates 2 3.642 1.821 1.62 0.207 Soil management practices 2 3.642 1.821 1.62 0.207 Residual 58 65.247 1.125 1.02 Total 71 71.261

Analysis of variance (adjusted for covariates) for OM_% Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 17.331 5.777 3.79 0.73 0.015 Elevation 2 39.735 19.867 13.05 0.94 <.001 Cropping System. Elevation 6 12.372 2.062 1.35 0.96 0.249 Covariates 2 1.244 0.622 0.41 0.667 Soil management practices 2 1.244 0.622 0.41 0.667 Residual 58 88.325 1.523 0.98 Total 71 159.938

Analysis of variance (adjusted for covariates) for pH

Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 0.5516 0.1839 0.46 0.73 0.712 Elevation 2 0.3995 0.1997 0.50 0.94 0.610 Cropping System Elevation 6 0.5978 0.0996 0.25 0.96 0.958 Covariates 2 2.0243 1.0122 2.52 0.089 Soil management practices 2 2.0243 1.0122 2.52 0.089

Residual 58 23.2666 0.4011 1.05 Total 71 27.0093

Appendix 7: Soil nutrients at soil - soil depth of 15-30cm

Analysis of variance (adjusted for covariates) for Ca (Cmolskg-1 )

Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 71.26 23.75 1.08 0.73 0.366 Elevation 2 28.94 14.47 0.66 0.94 0.523 Cropping System. Elevation 6 129.14 21.52 0.98 0.96 0.450 Covariates 2 89.08 44.54 2.02 0.142 Soil management practices 2 89.08 44.54 2.02 0.142 Residual 58 1278.76 22.05 1.03 Total 71 1548.67

Analysis of variance (adjusted for covariates) for K (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 69.997 23.332 3.81 0.73 0.015 Elevation 2 2.000 1.000 0.16 0.94 0.850 Cropping System. Elevation 6 30.829 5.138 0.84 0.96 0.546 Covariates 2 1.453 0.727 0.12 0.888 Soil management practices 2 1.453 0.727 0.12 0.888 Residual 58 355.538 6.130 0.97 Total 71 462.757

Analysis of variance (adjusted for covariates) for % P (ppm) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 29760. 9920. 1.57 0.73 0.207 Elevation 2 16713. 8356. 1.32 0.94 0.275 Cropping System. Elevation 6 45561. 7594. 1.20 0.96 0.319 Covariates 2 6265. 3132. 0.50 0.612 Soil management practices 2 6265. 3132. 0.50 0.612 Residual 58 367011. 6328. 0.98 Total 71 459219.

Analysis of variance (adjusted for covariates) Mg (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping_System 3 5.940 1.980 1.40 0.73 0.251 Elevation 2 4.322 2.161 1.53 0.94 0.224 Cropping_System.Elevation 6 10.987 1.831 1.30 0.96 0.272 Covariates 2 9.291 4.646 3.30 0.044 soil_mgt_practices 2 9.291 4.646 3.30 0.044 Residual 58 81.753 1.410 1.08 56

Total 71 107.581

Analysis of variance (adjusted for covariates) for N_% Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 0.024619 0.008206 1.35 0.73 0.268 Elevation 2 0.023633 0.011816 1.94 0.94 0.153 Cropping System. Elevation 6 0.008420 0.001403 0.23 0.96 0.965 Covariates 2 0.008631 0.004316 0.71 0.496 Soil management practices 2 0.008631 0.004316 0.71 0.496 Residual 58 0.353152 0.006089 0.99 Total 71 0.421899

Analysis of variance (adjusted for covariates) for Na (Cmolskg-1 ) Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 1.2608 0.4203 0.53 0.73 0.666 Elevation 2 0.5033 0.2516 0.31 0.94 0.731 Cropping System. Elevation 6 1.0771 0.1795 0.22 0.96 0.967 Covariates 2 3.9529 1.9764 2.47 0.093 Soil management practices 2 3.9529 1.9764 2.47 0.093 Residual 58 46.3800 0.7997 1.05 Total 71 52.8738

Analysis of variance (adjusted for covariates) for OM_% Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 11.490 3.830 2.28 0.73 0.089 Elevation 2 13.586 6.793 4.05 0.94 0.023 Cropping System. Elevation 6 5.283 0.881 0.52 0.96 0.787 Covariates 2 1.128 0.564 0.34 0.716 Soil management practices 2 1.128 0.564 0.34 0.716 Residual 58 97.340 1.678 0.98 Total 71 131.287

Analysis of variance (adjusted for covariates) for pH Source of variation d.f. s.s. m.s. v.r. cov.ef. F pr. Cropping System 3 0.8767 0.2922 0.98 0.73 0.408 Elevation 2 0.3051 0.1525 0.51 0.94 0.602 Cropping System. Elevation 6 0.7498 0.1250 0.42 0.96 0.863 Covariates 2 2.8911 1.4455 4.85 0.011 Soil management practices 2 2.8911 1.4455 4.85 0.011 Residual 58 17.2770 0.2979 1.13

Total 71 21.8276

Plate 1: a) A pitfall trap in a coffee- annual (bean) system, b) digging up soil within a quadrat before sorting for soil fauna

A b