Composition and Floral Resources of Bees and Butterflies in Kaya Muhaka Forest and Surrounding Farmlands, Kwale County, Kenya

David Odhiambo Chiawo (B.Ed. Science)

Reg. No. I56/5001/2003

Department of Zoological Sciences

Thesis submitted in partial fulfilment of the requirements for the award of the degree of Master of Science (Animal Ecology) in the School of Pure and Applied Sciences of Kenyatta University

November 2011

DECLARATION

Candidate

This is my original work and has not been presented for the award of a degree in any University or any other award.

David Odhiambo Chiawo

Signature...... Date......

Supervisors

We confirm that the candidate carried out this work under our supervision.

Prof. Callistus K.P.O. Ogol Department of Zoological Sciences Kenyatta University

Signature...... Date......

Dr. Mary W. Gikungu Centre for Bee Biology and Pollination Ecology Zoology Department National Museums of Kenya

Signature...... Date......

Dr. Esther N. Kioko Zoology Department National Museums of Kenya

Signature...... Date......

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DEDICATION

I dedicate this work to my wife Verrah and daughter Mitchelle.

ACKNOWLEDGEMENTS

I acknowledge the National Museums of Kenya (NMK) and the National Council for Science and Technology (NCST) for the financial support of this study. I am grateful to Dr. Mary W.

Gikungu, Centre for Bee Biology and Pollination Ecology, Zoology Department, NMK for facilitating this support. I acknowledge her for supervision and guidance throughout the study period. I owe much thanks to Prof. Callistus K.P.O. Ogol, Department of Zoological

Sciences, Kenyatta University for supervising this work and his leading role in facilitating the academic requirements of this study at Kenyatta University. I also owe the success of this work to Dr. Esther N. Kioko of Zoology Department, NMK for supervision and guidance throughout the study period. I thank the supervisors for their timely responses and being ready to discuss with me the work at frequent intervals. I thank NMK management for hosting me at Centre for Bee Biology and Pollination (CBBP) during the study period. The

CBBP supported my work with taxonomic skills, field materials and equipment; it also provided working space and resources that were useful for the bee identification. I do thank

Mr. Joseph Mugambi of Invertebrate Zoology laboratory, NMK for assisting me during the identification of butterfly samples. I owe thanks to Jane Macharia of Bee centre, NMK for organising my samples at the centre and making available the requirements during the study.

I acknowledge the support of Kaya elders and Kaya Muhaka community. They allowed me to access the forest and farms freely. I acknowledge the support of Abdalla Omari a residence of the local community for field assistance. I also thank Teachers Service Commission for granting me study leave during the period and Kenyatta University for accepting the study. I thank Dr. Itambo Malombe, Botany department for organising with the staff of herbarium,

NMK to assist me infloral resources identification. I also thank the CFCU staff at Ukunda for logistical assistance. I acknowledge the support of my family during the period. Above all, I thank God for the opportunity, strength, and protection throughout the study period.

TABLE OF CONTENTS

DECLARATION...... ii

DEDICATION...... iii

ACKNOWLEDGEMENTS ...... iv

TABLE OF CONTENTS ...... v

LIST OF TABLES ...... viii

LIST OF FIGURES ...... ix

LIST OF PLATES ...... xi

LIST OF APPENDICES ...... xii

ABBREVIATIONS AND ACRONYMS ...... xiii

ABSTRACT ...... xiv

CHAPTER ONE ...... 1

INTRODUCTION...... 1

1.1 Background ...... 1

1.2 Statement of the problem ...... 2

1.3 Research questions ...... 4

1.4 Null hypotheses ...... 4

1.5 Objectives ...... 4

1.5.1 General objective ...... 4

1.5.2 Specific objectives ...... 4

1.6 Justification of the study ...... 5

CHAPTER TWO ...... 6

LITERATURE REVIEW ...... 6

2.1 Vulnerability of bee population to habitat change ...... 6

2.2 Bee response to land use and habitat disturbance ...... 6

2.3 Butterfly response to land use and habitat disturbance ...... 7

2.4 Ecological and economic significance of insect pollinators ...... 7

2.5 Pollination crisis and conservation concern ...... 9

2.6 Conservation value of remnant indigenous Kaya forests ...... 10

2.7 Butterfly taxa and habitat preference ...... 11

2.8 Edge effects and tropical forest invertebrates ...... 12

2.9 Linking butterflies and bees to plant resources...... 13

CHAPTER THREE ...... 15

MATERIALS AND METHODS ...... 15

3.1 Study area...... 15

3.1.1 Biodiversity of the coastal forests ...... 16

3.1.2 Farmlands ...... 16

3.2 Study design ...... 16

3.2.1 Establishment of transects and sampling points ...... 17

3.2.2 Data collection ...... 21

3.3 Data management and analysis ...... 21

CHAPTER FOUR ...... 23

RESULTS ...... 23

4.1 Bee species richness and abundance ...... 23

4.1.1 Effect of increasing distance from forest core on bee species richness ...... 27

4.1.2 Effect of increasing distance from forest core on bee abundance ...... 27

4.2 Cluster analysis of bee composition based on Bray-Curtis ecological distance ...... 28

4.3 Butterfly species richness ...... 29

4.3.1 Effect of increasing distance from forest core on butterfly species richness ...... 31

4.3.2 Butterfly abundance ...... 32

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4.3.3 Effect of increasing distance from forest core on butterfly abundance ...... 33

4.4 Cluster analysis of butterfly composition based on Bray-Curtis ecological distance ...... 34

4.5 Effect of habitat type on the diversity of bees and butterflies ...... 35

4.5.1 Effect of increasing distance from forest core on bee diversity...... 37

4.6 Bee relative abundance in the study habitats ...... 38

4.7 Butterfly relative abundance in the study habitats ...... 40

4.8 Associated floral resources to bees and butterflies ...... 41

4.8.1 Important floral resources in Muhaka area ...... 45

4.9 Effect of floral resources richness on bee and butterfly species richness ...... 47

CHAPTER FIVE ...... 48

DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ...... 48

5.1 Effect of habitat type on bee abundance ...... 48

5.2 Effect of habitat type on butterfly abundance ...... 50

5.3 Effect of habitat type on bee and butterfly diversity...... 51

5.4 Effect of increasing distance from forest core on bees and butterflies ...... 54

5.5 Effect of habitat type on bee and butterfly relative abundance ...... 55

5.6 Effect of floral resources on bees and butterflies ...... 56

5.7 Conclusions ...... 58

5.8 Recommendations ...... 58

REFERENCES ...... 59

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LIST OF TABLES

Table 1: GPS coordinates of sampling points ...... 20

Table 2: Bee species composition ...... 23

Table 3: Butterfly species composition ...... 30

Table 4: P values for pair wise comparison of butterfly means ...... 36

Table 5: Butterfly diversity at varying distance from forest core ...... 37

Table 6: Bee floral resources ...... 41

Table 7: Butterfly floral resources ...... 43

Table 8: Bee species caught on flight ...... 44

Table 9: Butterfly species caught on flight ...... 44

Table 10: Floral richness and corresponding bee and butterfly species richness ...... 47

LIST OF FIGURES

Figure 1: Satelite map showing the location of study area and land use...... 15

Figure 2: Location of main transects ...... 18

Figure 3: Schematic illustration of belt transects and sampling points ...... 18

Figure 4: Satelite map showing study area and sampling points ...... 19

Figure 5: Bee species accumulation curve ...... 23

Figure 6: Relative abundance of three families of bees ...... 25

Figure 7: Total bee abundance per habitat ...... 25

Figure 8: Abundance of bee families per habitat ...... 26

Figure 9: Proportion of bee families in each habitat ...... 26

Figure 10: Effect of distance away from forest core on bee species richness ...... 27

Figure 11: Effect of distance away from forest core on total bee abundance ...... 28

Figure 12: Dendrogram of cluster analysis of bee species composition ...... 29

Figure 13: Butterfly species accumulation curve...... 29

Figure 14: Effect of distance from forest core on butterfly species richness ...... 31

Figure 15: Relative abundance of butterfly families in KMF and surrounding farmlands ...... 32

Figure 16: Overall butterfly abundance per habitat ...... 32

Figure 17: Butterfly families abundance per habitat...... 33

Figure 18: Effect of distance away from forest core on butterfly abundance ...... 34

Figure 19: Dendrogram of cluster analysis of butterfly species composition ...... 34

Figure 20: Rényi diversity profiles for separate habitats of bee data set ...... 35

Figure 21: Rényi diversity profiles for separate habitats for butterfly data set ...... 36

Figure 22: Effect of distance from forest core on bee diversity ...... 37

Figure 23: Effect of increasing distance from forest core on butterfly diversity ...... 38

Figure 24: Rényi evenness profiles of bee data set ...... 39

Figure 25: Overall rank-abundance curve showing the most abundant bee species ...... 39

Figure 26: Rényi evenness profiles of butterfly data set ...... 40

Figure 27: Overall rank-abundance curve showing the most abundant butterfly species ...... 41

Figure 28: Effect of floral resources richness on bee species richness ...... 47

LIST OF PLATES

Plate 1: Forest canopy cover at forest core (center) of KMF ...... 19

Plate 2: A site at forest edge of KMF ...... 19

Plate 3: A site in crop fields ...... 20

Plate 4: A site in fallow farmland ...... 20

Plate 5: A site in open fallow farmland ...... 20

Plate 6: Xylocopa caffra L. foraging on Agathisanthemum bojeri K...... 46

Plate 7: Cajanus cajan L., a bee pollinated local crop ...... 46

Plate 8: Jubernardia magnistipulata H., a forest tree pollinated by bees mainly Xlocopa sp. 46

Plate 9: Graphium angolanus G. foraging on Sida cordifolia L...... 46

Plate 10: Macrogalea candida S. foraging on Urena lobata L...... 46

Plate 11: Vigna unguiculata L., a common crop in the area that requires bee pollination. .... 46

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LIST OF APPENDICES

Appendix I: Checklist of bee species in KMF and surrounding farmlands ...... 65

Appendix II: Checklist of butterfly species in KMF and surrounding farmlands ...... 66

Appendix III: General list of floral resources in KMF and surrounding farmlands ...... 68

Appendix IV: Floral resources preference by bee species ...... 69

Appendix V: Distance matrix calculated using bray-curtis ...... 70

Appendix VI: Some common bee species collected in Muhaka, Kwale Kenya ...... 71

Appendix VII: Some forest dependent butterfly species in Kaya Muhaka forest ...... 72

Appendix VIII: Bee taxonomy certificate ...... 73

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ABBREVIATIONS AND ACRONYMS

ANOVA...... Analysis of Variance

CEPF...... Critical Ecosystem Partnership Fund

CFCU...... Coastal Forest Conservation Unit

GPS...... Global Positioning System

HSD...... Honest Significance Difference

IPI...... International Pollinators Initiative

KMF...... Kaya Muhaka forest

NMK...... National Museums of Kenya

TFCG...... Tanzania Forest Conservation Group

WWF-US...... World Wildlife Fund-United States

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ABSTRACT

The current global pollination crisis and the importance of insects in pollination service that maintains the native plant populations, agricultural enterprise, ecosystem resilience and food security do motivate the concern to conserve insect pollinators. Kaya forests are rich in biodiversity and endemism; they are potential sites for conservation of these pollinators in the coastal region of Kenya. However, they are threatened by illegal deforestation, charcoal burning, settlement and farming causing conservation threat to the pollinators. Understanding the composition of bee and butterfly communities and their response to the disturbance is essential if their conservation is to be successful in the area. The main objective of the study was to establish the composition of bees and butterflies along the disturbance gradient. The study examined the diversity and abundance of these pollinators and their floral resources along a disturbance gradient from the natural forest through the forest edge to farmlands. The study was carried out between April 2010 to September 2010 and data analysed using R software. Diversity, species richness, abundance and floral resources were examined in Kaya Muhaka forest, forest edge, surrounding fallow farmlands and crop fields. The survey was done at sampling points along two habitat zones in transition from the forest core to farmlands. Sampling was done using sweep nets within three permanent 50 m x 2 m belt transects at each sampling point. 36 belt transects were surveyed in 12 sampling points across the habitats for six months. Floral resources were identified and linked to the associated bees and butterflies. A total of 52 bee species and 66 butterfly species were recorded. The highest bee diversity was recorded in fallow farmlands and lowest in forest core. The diversity of bee species across the habitats was not statistically different. However, butterfly diversity was significantly higher in forest edge than in crop fields (P = 0.021). The lowest butterfly diversity was recorded in fallow farmlands. Both bees and butterflies were more abundant in the farmlands. Crop fields and forest edge were closely similar in bee and butterfly composition. Increasing distance from forest core had no significant effect on bee and butterfly diversity and abundance. The effect of floral resources richness on bee species richness was highly significant (P = 0.004). However, floral richness did not have significant effect on butterfly richness. Bees and butterflies were not evenly distributed in the habitats. These findings are important for understanding and management of insect pollinators in changing landscapes.

CHAPTER ONE

INTRODUCTION

1.1 Background

Biodiversity conservation calls for identification of biodiversity hotspots where exceptional concentrations of endemic species are undergoing continuous loss of their habitats; the sacred coastal Kaya forests are no exception. Sacred forest sites throughout the world are important for the preservation of plant and animal species useful to local people (Wadley and Colfer,

2004). However, more than 87% of the Earth‟s land surface is not currently protected

(Winfree et al., 2007). It is therefore pragmatic for conservation planning to consider species‟ use of anthropogenic habitats and to understand whether organisms that perform particularly important ecosystem functions persist in human-dominated ecosystems (Kremen et al.,

2007). The evidence that pollinators are declining in some parts of the world (Kearns et al.,

1998; Kremen and Ricketts, 2000) has attracted public attention and research.

Ecosystem services are critical to human survival (Kremen et al., 2002), a powerful argument for conserving the principal pollinators. However, it is important to note that conservation areas are no longer sufficient due to human activities, leading to increased focus on managed land for conservation (Tylianakis et al., 2005). In Africa and Madagascar, reliance on conserved areas such as National Parks will not be sufficient to preserve pollinator diversity in the face of increasing land use change (Eardley et al., 2009). Moreover, the community structure of forest insect pollinators is related to their host plants (Potts et al., 2003), meaning a strategic conservation plan should focus on both the insects and their associated floral resources. Past studies have revealed positive relationships between bee abundance and floral abundance, bee and floral diversity (Banaszak, 1996), butterfly diversity and floral abundance

(Potts et al.,2003). According to Pauw (2007) generalist pollinators are predicted to be

2 sensitive to human-caused disruption, and their early loss will trigger a cascade of linked declines among the multiple plant species that they pollinate. Kremen et al. (2007) explains that pollination services are provided by varied wild, free-living organisms but chiefly bees and also many butterflies and commercially managed bee species (primarily the honey bee,

Apis mellifera L.). Bees form keystone mutualisms with their host plants maintaining the biodiversity of most terrestrial eco-systems (Stubbs et al., 1997).

In spite of the pollinators‟ ecological significance, land use has changed the landscape structure in ecosystems influencing their temporal and spacial availability of food, nesting and mating sites (Kremen et al., 2007). The recent large scale parallel decline of plants and pollinators is a reinforcement to the concern that pollination as an ecosystem service is at risk

(Biesmeijer et al., 2006). The pollinator declines and losses of pollination services have been identified in the context of habitat destruction and land use intensification (Steffan-Dewenter and Westphal, 2008). Despite the ongoing concerns and controversy over a putative „global pollination crisis‟ there is little information on the response of bees, the most important group of pollinators, to land-use change (Brosi et al., 2008). Given the importance of bees for the maintenance of native plant populations, human agricultural enterprise and attached commercial value, it is vital that their complex responses to ongoing global changes, particularly in the tropics be investigated (Brosi et al., 2008) in order to understand how their diversity, distribution and community composition are affected. The study focuses on bees and butterflies the predominant and most economically important pollinators in the region.

1.2 Statement of the problem

The decline in bee populations is now a worldwide phenomenon. In Africa and Kenya in particular, a very large number of bee species are undescribed despite the increasing trend in

3 habitat destruction and degradation. Bees and butterflies offer essential pollination service linked to food production and ecosystem regeneration. Bees are also important in honey production while butterflies promote eco-tourism and foreign exchange. The two insect groups have potential commercial value and improved livelihoods for the Mijikenda community living around the Kaya forests. Despite the high biodiversity and endemism of the

Kaya forests, they are threatened by illegal deforestation, settlement and farming causing a conservation threat to these commercial insects. Kaya Muhaka forest (KMF) is outstanding among the biodiversity reserves of the coastal forest remnants due to high diversity and endemism of butterflies. Although this concept has strong resonance and logic, ecosystem- wide studies on the commercial insects of the Eastern African Coast in general, and the region in particular, is unfortunately limited, and yet the emerging picture is alarming, with entire sets likely to disappear. No study has been done to link insect pollinators of this area to their associated floral resources with bee data completely lacking.

Even though KMF is a protected area, human disturbance, habitat change and land use contexts in the neighborhood may intensify the pollinator decline due to shrinking natural habitat and food resources. Bees being more vulnerable to such changes due to their genetic and demographic characteristics stand to be most affected. The problem to be addressed by this study is lack of tangible baseline data on bees, butterflies and their floral resources in the region. The study is motivated by the need for an inventory for these insects and their associated floral resources in order to make a more informed, pragmatic and comprehensive conservation plan. Regeneration, conservation, monitoring and sustainable utilization programs for such species and their floral resources can then be developed, which is critically crucial for the ecosystem resilience and livelihoods.

1.3 Research questions

i. What is the diversity of bees and butterflies in the forest core (center), forest edge,

fallow farmlands and crop fields?

ii. What is the relative abundance of bees and butterflies in the habitats? iii. What is the relationship between species richness of the insects and floral resources

richness?

1.4 Hypotheses

i. There is no significant difference in species diversity of bees and butterflies in the

forest core, forest edge, fallow farmlands and crop fields.

ii. Bees and butterflies are evenly distributed among forest core, forest edge, fallow

farmlands and crop fields. iii. There is no correlation between species richness of the insects and richness of the

floral resources.

1.5 Objectives

1.5.1 General objective

To establish the composition and floral resources of bees and butterflies in Kaya Muhaka

Forest and surrounding farmlands in Kwale county, coastal Kenya for improved livelihoods and biodiversity conservation.

1.5.2 Specific objectives

i. To determine the diversity of bees and butterflies in the forest core, forest edge and

surrounding fallow farmlands and crop fields. ii. To determine the relative abundance and distribution of bees and butterflies in the

various KMF habitats.

5 iii. To identify the floral resources and determine the relationship between their richness

and richness of the insect pollinators.

1.6 Justification of the study

A global pollination crisis has been recognized (Allen-Wardell et al., 1998; Kearns et al.,

1998; Tylianakis and Tscharntke, 2005) and the international pollinator initiative (IPI) points to a lack of baseline ecological data for plant-pollinator interactions on which to develop strategies for integrated management of landscapes (Potts et al., 2003). The current pollination crisis emphasizes the importance of understanding the fundamental determinants of plant-pollinator community structure and the need to document their floral requirements

(Sāo Paulo declaration, 1999) to underpin any conservation efforts. Bees and butterflies provide pollination service which is essential to human welfare; pollination provides significant and measurable benefits to humanity (Kremen et al., 2002), this is a potential economic argument for their conservation. Pollinators play a crucial role in ecosystem processes and contribute to the maintenance of ecosystem function (Potts et al., 2003); they are a functional group with high relevance for ensuring cross-pollination in wild plant populations and yields in major crops. Data on their relative abundance and diversity gives an indication of pollinator force (Kevan, 1999). It is important to note that Kaya Muhaka Forest

(KMF) is an isolated habitat, which may reduce species richness and abundance of pollinator guilds, change the foraging behaviour of flower-visiting insects, disrupt plant-pollinator interactions, and reduce seed set and gene-flow of isolated plant population (Didham et al.,

1996). The study will be useful in that it will develop an inventory of commercial insects and associated flora for conservation and improvement of livelihoods in KMF.

CHAPTER TWO

LITERATURE REVIEW

2.1 Vulnerability of bee population to habitat change

Human impacts have modified the landscape through fragmentation, degradation and destruction of natural habitats and the creation of new anthropogenic habitats. The changes in land use and landscape structure influence pollinators at individual, population and community scales. Kremen et al. (2007) explains that at population level, genetic and demographic characteristics may predispose bee populations to be particularly vulnerable to habitat and landscape changes that reduce population size. Zayed and Packer (2005) reports two reasons for their vulnerability. First, bees are haplodiploid, which reduces the effective population size to at most 3/4 that of equivalently sized diploid populations with approximately even sex ratios. Second, single-locus sex determination contributes to reduced population size because homozygotes at the sex locus become sterile diploid males.

2.2 Bee response to land use and habitat disturbance

The effects of high quality habitats are likely to be more effective in enhancing pollinator diversity and abundance, when ecological restoration sites are available in the close vicinity

(Steffan-Dewenter and Westphal, 2008). Activities associated with such high-intensity land uses, such as pesticide application, tilling, other soil disturbance, and the clearing of native habitat from local to landscape scales, may make it difficult for bees of nearly any guild to persist (Kremen et al., 2007). However, bee communities appear to have some degree of resilience to land-use change, as diverse bee faunas have persisted over decadal time scales in agricultural landscapes in Poland (Banaszak, 1992). It is therefore possible that some modified habitats may support more species than has been previously assumed (Driscoll,

2005). On the contrary, stingless bee abundance is dependent on the proportion of forested

7 area in the surrounding landscape (Brosi et al., 2008). Disturbed forests tend to have greater absolute bee species richness (α-diversity) (Liow et al., 2001). They may attract more

“wanderer” bees (those that do not reside within the forest) with potentially large foraging ranges like Amegilla and Xylocopa spp. However, undisturbed lowland primary and secondary forests tend to have high absolute abundance of bees (Liow et al., 2001).

2.3 Butterfly response to land use and habitat disturbance

According to Davros et al. (2006) some butterfly species are disturbance-tolerant and can be found in areas altered by humans and are effectively tolerant to removal of the native vegetation. However, habitat-sensitive species have more specific requirements for habitat and vegetation composition to suit the needs of other life stages and are often found only in relatively natural areas with native vegetation. Studies by Steffan-Dewenter and Tscharntke

(1997) indicated that butterfly richness did not change with vegetation succession over time but species composition was affected significantly.

2.4 Ecological and economic significance of insect pollinators

Estimates of the value of pollination done by bees have varied and are primarily based on. A. mellifera. Bees also aerate soil by digging nesting burrows, consume honeydew, nectar, and pollen; fertilize plants with their wastes; pollinate plants; and serve as food for other organisms in numerous habitats (Sheffield et al., 2003). The value of crop pollination by the most important managed pollinator, the honey bee A. mellifera, is estimated to be 5-14 billion dollars per year in the United States alone (Kremen et al., 2002) and a global estimate of US$

65-70 billion (Hartmann, 2004). Recent reviews quantify that 35% of the crop production volume and 70% of major global crops rely on animal pollination (Klein et al., 2007). In agricultural regions, bees (Hymenoptera: Apoidea) have long been recognized as being vital for successful fruit production (Sheffield et al., 2003). According to Potts et al. (2003) it is

8 estimated that 60-70% of flowering plant species are dependent upon insects for pollination worldwide with bees being the principal pollinating group in most geographic regions and the non-Apis species maintaining the integrity of many natural communities. Bees are more effective pollinators for other crops including alfalfa, an important forage crop and cover crop contributing to soil fertility, and many orchard crops (O'Toole, 1993).

In Ethiopia, the largest honey producer in Africa and the 10th largest honey producer in the world; the total honey production is estimated up to 24 tonnes. About 80% of this goes into preparation of a national drink“Tej” (honey wine). Ethiopia is the fourth largest producer of beeswax in the world, which is exported mainly to Japan, Germany, Netherlands and the

USA (Hartmann, 2004). Further economically important honey products are propolis and pollen, and others that are used in pharmacy, cosmetic and colour industry (Hartmann, 2004).

In xeric areas and Mediterranean scrub communities, bees are present in particularly high diversity and are the principal pollinators, contributing to the preservation and reproduction of the natural vegetation, which prevents erosion and provides the cover and food for native wildlife (Neff and Simpson, 1993; Michener, 2000). In view of their effectiveness as pollinators, bees are a prime example of “keystone mutualists", being essential for the maintenance of ecosystem integrity and of angiosperm diversity (LaSalle and Gould, 1993).

On the other hand, butterfly taxa are used increasingly as habitat or environmental quality indicators (Hamer et al.,1997; Hill, 1999; Fiedler and Schulze, 2004). Currently butterflies have greater commercial returns to some Kenyan communities. Butterfly farming has improved the livelihood of the local people in Taita Hills where farming of 14 species of

Taita Hills endemics Cymothoe teita van Someren and Papilio desmondi teita van Someren earned them up to US$ 600 from the sale of 61 percent of 1052 pupae after six months of rearing (TFCG, 2007).

2.5 Pollination crisis and conservation concern

Pollination provided by wild bees is likely being reduced in many of the areas where they could be contributing to crop production with pollination-related problems within natural and agricultural ecosystems becoming more common (Buchmann and Nabhan, 1996).

Approaching such issues by documenting which species are involved is a key step to facilitate their preservation and management (Danks, 1994). Moreover, numbers of commerciallymanaged colonies of A. mellifera have also declined inmany parts of the world

(Kremen et al., 2007).

Torchio (1990) explains that out of the approximated 20,000 to 30,000 species of bees,only a few species have been domesticated and are available commercially, e.g., A. mellifera, the bumble bee Bombus impatiens Cresson, and the alfalfa leaf cutting bee, Megachile rotundata

Fabricus. These concerns about the loss of pollinators and the services they provide have grown over the last decades (Kearns et al., 1998), but only a few studies have been published for Kenya (Gikungu, 2002; Eardley et al., 2009). The concerns are warranted based on recent evidence of pollinator declines (Biesmeijer et al., 2006). The decline may be aggravated at the coastal Kenya due to habitat fragmentation, making threatened species within key sites highly vulnerable to extinction. Agricultural encroachment, timber extraction and charcoal burning are the greatest threats to habitat in this region, although weak management capacity within government and communities is a serious issue (CEPF, 2005).

Bees are the most highly adapted of all flower visitors, making them most successful pollinators. Owing to their high dependence on nectar, pollen, and oil from flower resources for feeding and larval food, bees exhibit among the highest floral visitation rates in the world, making them the single most important group of pollinators (Neff and Simpson, 1993).

However, the pollination success of insect-pollinated plant species is usually not dependent on single, highly specialized pollinator species, but rather on a diverse community of pollinators (Steffan-Dewenter and Westphal, 2008). This means the current evidence of elevated pollinators extinction rates across all taxa (Kremen et al., 2007) puts pollination as an ecosystem service at risk (Biesmeijer et al., 2006). According to Sheffield et al. (2003) there is historic knowledge of the importance of bees in agricultural plant communities, but only recently there has been an appreciation of the fragility of many plant-pollinator relationships. Furthermore, very little is known about how stingless bees respond to forest disturbance caused by human activities (Eltz et al., 2002).

To effectively conserve the pollinators in human dominated habitats, there is need for an ecosystem approach to management of crop fields and semi-natural habitats in order to sustain the availability of their floral resources in different seasons of the year. Floral community composition, the quantity and quality of forage resources present, and the geographic locality do organize bee communities at various levels and act in specific ways to modulate the diversity of the local geographic species pool (Potts et al., 2003). Therefore, the pollinator crisis exemplifies the intimate relationship existing between the welfare of natural environments and their biodiversity and the needs of sustainable agriculture.

2.6 Conservation value of remnant indigenous Kaya forests

Remnant indigenous coastal forests are important conservation corridors which may attract ecological interactions between plants and insects (Bullock and Samways, 2005). Despite the relative small size of the Kaya forests, they have high rarity and conservation values

(Robertson and Luke, 1993). Majority of plant species in these forests are woody but there are also endemic climbers, shrubs, herbs, grasses and sedges (Burgess et al., 2000). The

11 forests are also known for higher endemism of invertebrate groups such as millipedes, molluscs and forest butterflies (Burgess et al., 2000). Kaya Muhaka forest which is one of the sacred forests of the Mijikenda community in Kwale county is an isolated lowland coastal forest classified as “Wetter mixed semi-deciduous forest” with a high Lepidoptera diversity and endemism (Lehmann and Kioko, 2005). Lepidoptera diversity and endemism is high in

KMF including species with a western and central Africa distribution, as well as the Kenyan endemic montane subspecies Charaxes acuminatus shimbanus van Someren (Lehmann and

Kioko, 2005).

2.7 Butterfly taxa and habitat preference

Within the family Nymphalidae, members of the subfamilies Satyrinae and Morphinae have relatively broad wings, favouring slow agile flight, and are often encountered beneath the canopy in dense unlogged forests. These species with greater shade preference have significantly narrow geographical distributions. Open gaps in unlogged forests attract widespread species of Nymphalinae and Charaxinae (Hamer et al., 2003). However, species in the subfamilies Nymphalinae and Charaxinae with broad thoraces have rapid powerful flight, and are often encountered in more open areas (Hill et al., 2001; Schulze et al., 2001).

Hamer et al. (2003) explains that selective logging in primary forests is associated with loss of environmental heterogeneity, primarily affecting the relative abundance of species rather than species richness; suggesting preservation of environmental heterogeneity as far as possible in any conservation management. Butterflies with strong powers of flight and open population structures such as the large white (Pieris brassicae L.), the brimstone (Gonepteryx rhamni L.) and the small tortoise shell (Aglais urticae L.) are unlikely to be constrained by a lack of shelter, allowing them to exploit resources effectively in areas inaccessible to other less vagile species (Feber et al., 1996). Nonetheless, floristic heterogeneity within a habitat

12 has an influence on butterfly species composition and abundance (Namu, 2005) with intermediate disturbance increasing species richness in tropical forests (Sheil and Burslem,

2003).

Butterfly taxa appear to be negatively impacted by fragmentation, exhibiting population declines and even extinction (Shahabuddin and Terborgh, 1999). According to Foggo et al.

(2001) it is generally assumed that large species are more sensitive to fragmentation and therefore need larger reserve sizes than small species. They are also thought to be more sensitive to fragmentation because of greater space use and food requirements; this assumption ignores the fact that large species may be able to use multiple patches because of their higher mobility (Foggo et al., 2001). Evidence from experiments suggests that field edges support breeding populations of most of the butterfly species rather than simply attracting aggregations of mobile individuals (Feber et al., 1996). They are likely to be most effective as supplements to, or replacements for, established plant species, where sources of suitable colonists have been eliminated and the vegetation is impoverished or dominated by annuals (Smith et al., 1994). Such wild flower mixtures will be most beneficial to adult butterflies if they include early and late flowering species to provide nectar throughout the seasons (Feber et al., 1996).

2.8 Edge effects and tropical forest invertebrates

Edge effects in landscape ecology are essentially the biotic and abiotic contrasts between adjacent habitat types (Foggo et al., 2001). They are causal mechanisms influencing behaviour, distribution, species abundance and other higher order assemblages. They may therefore exert an influence that extends beyond the limits of the physical edge itself. In most terrestrial ecosystems, edges can be defined as the physical boundaries between plant

13 community types (Samways, 1994), characterised by changes in factors such as floral structure, composition, and microclimate (Foggo et al., 2001). Three mechanisms have been cited most commonly to explain increased abundance of forest insects near edges; spill-over, edges as enhanced habitat, and complementary resource distribution (Ries and Sisk, 2004).

According to Shmida and Wilson (1985) increased abundance near edges have often been attributed simply to spill-over, which occur when individuals disperse into non-habitat by crossing the boundary from their preferred habitat but are not likely to penetrate very deeply into a patch of non-habitat.

2.9 Linking butterflies and bees to plant resources

Presence of appropriate plants is obviously important in determining the suitability of a given habitat for a butterfly species (Sharp et al., 1974). According to Ehrlich and Gilbert (1973), plant resource distribution may be of critical importance in butterfly population structure.

Contrary to this opinion; Sharp et al. (1974) found no relationship between butterfly population structure and total plant diversity. However, according to Yamamoto et al. (2007) both larval and adult stages of butterflies depend almost entirely on specific plants for their dietary requirements and therefore supports that resource abundance explains the variation in the abundance and species richness of herbivorous insects. The influence of plant associations on butterfly distribution seems to be determined by the range of the animals, the distribution of particular plants of critical importance to them and the predictability of their environment. Studies conducted on both wide-ranging and rather sedentary butterflies where food sources were locally distributed have shown strong associations between the distribution of the butterflies and of the nectar sources (Sharp et al., 1974).

Competition theory for diversity regulation predicts that the diversity of consumers and resources are positively correlated, as should consumer and resource abundance (MacArthur,

1972). In Mt. Carmel National reserve in Israel, the abundance A. mellifera was found to be closely related to resource availability even though the family Apidae had no close linkage to environmental variables. In contrast, the Megachilidae appeared to be organized by both nectar and pollen resources; species richness was related to floral diversity. The diversity within Andrenidae was positively associated with floral diversity (Potts et al., 2003). The linkage between bee and flower diversity is accounted by the strong associations found within the Andrenidae and Megachilidae, which appear to be absent from the Apidae (Potts et al., 2003). This study explains further that the absolute diversity of bees is strongly related to the diversity of flower species, especially annuals, and it is the variety of nectar foraging resources that appears to be the defining factor. Nonetheless, the overall bee abundance is a positive function of the abundance of flowers in a particular habitat. An understanding of the underlying ecological interactions between plants and pollinators at a variety of spatial scales is essential for the conservation and restorationof the threatened communities found worldwide (Sāo Paulo Declaration, 1999). This understanding will be useful in conservation planning for bees and their associated floral resources in KMF and surrounding farmlands.

CHAPTER THREE

MATERIALS AND METHODS

3.1 Study area

The study was conducted at the sacred Kaya Muhaka forest (KMF) situated on the coastal plains of Kenya (East Africa) at a geographical location of 04° 18‟ S - 04° 38‟ S; 39° 33‟ E -

39° 53‟ E and surrounding farmlands (Figure 1). KMF covers about 130-150 ha and is located 32 km from Mombasa town at an altitude of 20 - 40 m ASL. Kaya forests are residual patches of once extensive diverse lowland forest of Eastern Africa. It is a protected area and managed by Coastal Forest Conservation Unit (CFCU) of National Museums of Kenya

(NMK) in conjunction with the local community.

Figure 1: Satelite map showing the location of study area and land use.

3.1.1 Biodiversity of the coastal forests

Coastal forests stretch from Kenya to Tanzania and Islands of Zanzibar and Pemba. The forests host more than 4500 plant species and 1050 plant genera with around 3000 species and 750 genera occurring in the forest. At least 400 plant species are endemic to the forest patches and another 500 are endemic to the intervening habitats that make up 99 % of the eco-region area (WWF-US, 2003).

3.1.2 Farmlands

The surrounding farmlands are characterised by small scale farming of subsistence crops such as cassava, cowpea, maize and rice. Also found sparsely distributed in these farms is Cajanus cajan. Major commercial crops include, coconut, citrus, cashewnut and mangoes. Fallow farmland were characterised by a mix of open grasslands, shrubs, mango and cashew nut trees. Farmlands close to settlements are dominated by coconut plantations.

3.2 Study design

The main focus of this study were bees, butterflies and their floral resources. Surveys were conducted along two transects established from the forest core and tranversed through the forest edge to the farmlands. Sampling points were located at an interval of 0.5 km along two

2.5 km transects (Figures 2 and 3) in the forest core (Plate 1), forest edge (Plate 2) and farmlands. The farmland was categorised further into fallow farmlands and crop fields due to their ecological differences (Plates 3, 4 and 15).

A set of 3 parallel 50 m x 2 m belt transects located 50 m apart were laid with one passing through the center of the point and one on each side as shown in figure 3. Individual bees and butterfly samples were coded to be able to associate them with their habitats and floral resources. Belt transects are most effective active sampling methods for bees, as compared

17 with timed observations of quadrats or sweeping vegetation (Banaszak, 1996). Bee samples were collected in vials containing cotton wool soaked with ethyl acetate to kill the bees. Bees collected for each day were mounted every evening to avoid loss of taxonomic structures.

Butterflies were killed by gently pressing the thorax and placed in envelopes for transfer to the laboratory at NMK. In the laboratory, they were relaxed, pinned and set in the setting boards and placed in oven for 48 hours to ensure they were fully dry. They were then pinned in insect storage boxes. Collections were first pooled according to sampling points then habitats. Flower cutting and a small branch of plant species supplying the floral resources were sampled and given the same code as that of the associated bee or butterfly to be able to document insect-plant association correctly (Gikungu et al., 2011; Gikungu, 2006). It was assumed that the samples collected did not affect the population of the insect species. Bee and butterfly samples were identified to species level at the entomology section of the NMK.

Plant materials were pressed and taken for identification at NMK Herbarium.

3.2.1 Establishment of transects and sampling points

Two transects were established from the forest core through the forest edge to the farm lands.

The transects were established across four habitat types; forest core, forest edge, fallow farmland and crop fields (Figure 2). Location of the two transects wasbased on vegetation structure and land use types. Sampling points were located along the two main transects as shown in figure 3. Six sampling points were located on each transect (Figure 4) at global positioning system coordinates shown in table 1.

Figure 2: Location of main transects

The points were sampled in the same order in the six months of collection period for uniformity. For each sampling day, the selection of sampling points were randomized along the main transect as described by Winfree et al. (2007) to limit temporal effects. To adequately sample species with different diurnal patterns, sampling was done between 8.30 a.m. – 12.30 a.m. and 2.00 p.m. – 4.00 p.m. during sunny and partly cloudy days when bees and butterflies actively forage.

Figure 3: Schematic illustration of belt transects and sampling points

Figure 4: Satelite map showing study area and sampling points

Plate 1: Forest canopy cover at forest core (center) of KMF Plate 2: A site at forest edge of KMF

Plate 3: A site in crop fields Plate 4: A site in fallow farmland

Plate 5: A site in open fallow farmland

Table 1: GPS coordinates of sampling points

GPS coordinates of sampling points A1 4° 19' 72" S 39° 31' 59" E B1 4° 20' 16" S 39° 31' 44" E A2 4° 19' 68" S 39° 31' 41" E B2 4° 20' 08" S 39° 31' 30" E A3 4° 19' 65" S 39° 31' 17" E B3 4° 20' 02" S 39° 31' 02" E A4 4° 19' 57" S 39° 30' 91" E B4 4° 19' 97" S 39° 30' 75" E A5 4° 19' 48" S 39° 30' 64" E B5 4° 19' 93" S 39° 30' 45" E A6 4° 19' 40" S 39° 30' 36" E B6 4° 19' 90" S 39° 30' 18" E

3.2.2 Data collection

All foraging bees and butterflies encountered along the 50 m x 2 m belt transects were collected using a sweep net (hand netting) within a standard 20 minutes sampling time per belt for the diversity and abundance data as described by Potts et al. (2003) and Banaszak

(1996). Each belt transect was surveyed three times a month for 6 months for the purpose of replication. Sampling was done from April 2010 to September 2010 covering the wet and dry periods. The number of bees visiting collected at the sampling points during the sampling period was considered an estimate of bee abundance at the points (Diego and Simberloff,

2002). Butterfly abundance was estimated in the same way. To assess floral resources richness at each site, plant species with open flowers were counted and recorded at each sampling point. Forest data including bees, butterflies and floral resources were from the understory.

3.3 Data management and analysis

Diversity was determined based on species richness; α Shannon‟s diversity index. Evenness index (J) was used to measure the relative abundance of bees and butterflies in the study area.

Renyi diversity and evenness profiles were used to compare the diversities and evenness of the habitats. Renyi technique characterizes the diversity of a community by (a scale- dependent) diversity profile rather than expressing it simply as a numerical value (Renyi,

1961). Therefore, it is robust and takes into account both rare and dominant species in the diversity analysis (Renyi, 1961; Tothmeresz, 1998). Renyi diversity profiles of the separate habitat types were used to order the habitats based on species richness. A habitat with diversity profile starting at a higher level than others was considered richer. Profiles above others along their range from start to end indicated higher diversity or evenness of the habitat

(Kindt and Coe, 2005). Cluster analysis was used to analyse the ecological distance among

22 the habitats to depict their similarity in species composition. One-way analysis of variance

(ANOVA) was used to compare the diversity and relative abundance of the insects among the habitats. Tukey's honest-significance difference test (HSD test) was used in comparisons of means. The relationship between species richness of insects and floral resources was tested using linear regression analysis. Simple linear regression was also used to test the effect of increasing distance from forest core along the disturbance gradient on species diversity, richness and abundance. Species rank-abundance curves were used to identify the dominant butterfly and bee species and to show the overall pattern of species evenness. Bee and butterfly data sets were analyzed separately using R 2.12.1 program. Species abundance distribution was presented in bar graphs with standard error bars. Numerical values of

Shannon-Wiener diversity index (H') and Evennes index (J) were calculated using the formulas according to Krebs (1993). The Renyi diverisity formula as expressed by

(Tothmeresz, 1998) is shown below.

Renyi diversity formula;

H = ln (∑Pi)/1-

Where; ln is the natural logarithm, ∑ Pi is the summation of the proportions of each species and - is the scale parameter whose values vary from 0 to infinity, excluding 1.

Shannon-Wiener diversity index (H') formula;

S H' = -∑Pi ln Pi i= 1

Where Pi is the proportion of species i and ln is the natural logarithm of the proportion with i

= 1, 2 .....S. S is the total number of species present.

Evennes (J) index formula; J = H'/ log S

Where H' is the Shannon-Wiener diversity index and S is the species richness.

CHAPTER FOUR

RESULTS

4.1 Bee species richness and abundance

A total of 755 bees were collected in forest core, forest edge, fallow farmlands and crop fields. Fifty two species were recorded (Figure 5).

Figure 5: Bee species accumulation curve

Bees collected were from Apidae, Halictidae and Megachilidae (Table 2).

Table 2: Bee species composition

Bee Family Bee species Apidae Amegilla mimadvena Cockerell Amegilla sp. 1 Amegilla sp.2 Amegilla sp.4 Amegilla sp. 6 Apis mellifera Linnaeus Braunsapis sp. Ceratina sp. 1 Ceratina sp. 2 Ceratina sp. 3

Ceratina sp. 4 Ceratina sp. 5 Ceratina sp. 6 Ceratina sp. 7 Dactylurina schmidti Stadelmann Hypotrigona sp. 1 Hypotrigona sp. 2 Macrogalea candida Smith Meliponula ferruginea Lepeletier Pachymelus sp. Thyreus sp. Xylocopa caffra Linnaeus Xylocopa flavicollis DeGeer Xylocopa flavorufa DeGeer Xylocopa hottentota Smith Xylocopa nigrita Fabricius Xylocopa scioensis Gibodo

Halictidae Halictus sp. Lasioglosum sp. Lipotriches sp. 1 Lipotriches sp. 2 Lipotriches sp. 3 Lipotriches sp. 4 Nomia sp. Pseudapis sp. Pseudapis sp. 2 Sphecodes sp. Steganomus sp. Unidentified 1 Unidentified 2

Megachilidae Euaspis sp. Coelioxys sp. Heriades sp. Megachile discolour Smith Megachile felina Gerstacker Megachile sp. 2 Megachile sp. 3 Megachile sp. 5 Megachile sp. 7 Megachile sp. 8 Megachille sp. 6 Pachyanthidium sp.

Apidae family were most abundant with a much greater proportion of 76%, followed by

Halictidae at 14% and then Megachilidae at 10% (Figure 6).

Figure 6: Relative abundance of three families of bees

The highest overall bee abundance was recorded in fallow farmlands followed by crop fields then the least number in forest core (Figure 7).

Figure 7: Total bee abundance per habitat

Halictidae was most abundant in fallow farmlands while Megachilidae were most abundant in the crop fields. Forest core had the least abundance for the three bee families. The highest abundance of Apidae was recorded in crop fieldsthen forest edge (Figure 8).

Figure 8: Abundance of bee families per habitat

Apidae had the largest proportion in all the habitats while Megachilidae had the least proportion at the forest edge (Figure 9).

Figure 9: Proportion of bee families in each habitat

4.1.1 Effect of increasing distance from forest core on bee species richness

Forest edge recorded the highest bee species richness while the lowest was recorded at the forest core. There was marked reduction in species richness with increasing distance from the forest core especially from 1.5 km. Increasing distance from forest core had no significant

2 effect on bee species richness (F1, 4 = 0.001, P = 0.977, R = 0.00025, y = -0.1714x + 26.048)

(Figure 10).

Figure 10: Effect of distance away from forest core on bee species richness

4.1.2 Effect of increasing distance from forest core on bee abundance

The highest bee abundance was 215 individuals recorded at 1 km from the forest core along the disturbance gradient to crop fields. There was apparent reduction in bee abundance from

215 to 60 individuals from 1 km to 2.5 km from the forest core. But Overall, increasing distance from forest core had no significant effect on total bee abundance (F1, 4 = 0.389, P =

0.567, R2 = 0.089, y = -23.029x + 154.62) (Figure 11).

Figure 11: Effect of distance away from forest core on total bee abundance

4.2 Cluster analysis of bee composition based on Bray-Curtis ecological distance

Crop fields and forest edge had closely similar bee species composition. Fallow farmland shared more species with crop fields and forest edge than forest core as shown by the clusters in figure 12. Habitats which share most of their species have smaller ecological distance between them while those with a few species in common have larger ecological distance

(Kindt and Coe, 2005). Therefore, crop fields and forest edge shared more species in common.

Key: X1-Crop fields, X2-Fallowfarmland, X3-Forest core, X4-Forest edge

Figure 12: Dendrogram of cluster analysis of bee species composition

4.3 Butterfly species richness

A total of 545 butterflies representing 5 families, namely Papilionidae, Hesperiidae,

Nymphalidae, Lycaenidae and Pieridae were collected and 66 species identified (Figure13 and table 3).

Figure 13: Butterfly species accumulation curve

Table 3: Butterfly species composition

Butterfly Family Butterfly Species Hesperiidae Spilia sp. Lycaenidae Anthene demarah Guerin-Meve Anthene sp. Azanus natalensis Trimen Baliochila sp. Leptotis pirithous Linnaeus Spindasis homeyeri Dewitz Spindasis victoriae Butler Teriomima subpunctata Kirby

Nymphalidae Acraea acrita Hewitson Acraea braeasia Godman Acraea eponina Cramer Acraea natalica Boisduval Acraea satis Ward Amauris niavius Linnaeus Amauris ochlea Boisduval Bebearia chriemhilda Staudinger Bicyclus safitza Hewitson Bicyclus sp. Byblia antavara Boisduval Byblia ilithyia Drury Chraxes contrarius Weymer Coenyropsis carcassoni Kielland Danaus chrysippus Linnaeus Euphaedra neophron Hopffer Euryphura achlys Hopffer Eurytela dryope Cramer Hypolimnas anthedon Douleday Hypolimnas deceptor Trimen Hypolimnas misippus Linnaeus Hypolimnas usambara Ward

Nymphalidae Junonia oenone Linnaeus Junonia natalica Felder Melanitis leda Linnaeus Neptis goochi Trimen Neptis kiriakoffi Overlaet Neptis saclava Hopffer Pardopsis puntatissima Rothschild Phalanta phalantha Drury Physcaeneura leda Drury Salamis parhassus Bonte & Van Dyck Tirumala petiverana Klug Ypthima asterope Klug Salamis cacta Fabricius Pseudacraea lucretia Cramer

Papilionidae Graphium angolanus Goeze Graphium antheus Cramer Graphium colona Ward

Graphium kirbyi Hewitson Papilio demodocus Esper Papilio dardanus Brown

Pieridae Appias epaphia Boisduval Appias lasti Grose-Smith Belenois crawshayi Butler Belenois creona Cramer Belenois thysa Hopffer Catopsilia florella Fabricius Colotis antevippe Lucas Colotis euippe Linnaeus Colotis ione Godart Colotis vesta Reiche Eurema brigitta Stoll Eurema hecabe Butler Leptosia acesta Bernardi Nepheronia argia Fabricius Nepheronia thalassina Boisduval

4.3.1 Effect of increasing distance from forest core on butterfly species richness

The highest butterfly species richness was recorded at the forest edge, 0.5 km from the forest core. Butterfly species richnes reduced with increasing distance into the crop fields.

2 However, this reduction was not statistically significant (F1, 4 = 7.165, P = 0.060, R = 0.642, y = -9.714x + 35.476) (Figure 14).

Figure 14: Effect of distance from forest core on butterfly species richness

4.3.2 Butterfly abundance

The family Nympalidae was most abundant and dominant across all habitat types (Figure 15).

Figure 15: Relative abundance of butterfly families in KMF and surrounding farmlands

Crop fields had the highest abundance of butterfly species followed by fallow farmlands then forest edge. Forest core recorded the least abundance of butterflies. There was a trend of butterfly abundance from forest core to crop fields (Figure 16).

Figure 16: Overall butterfly abundance per habitat

The family Nymphalidae was dominant in all the study sites with peak abundance in crop fields while Hesperiidae was only recorded at the forest edge. Pieridae was the second dominant family across all the habitat types. Papilionidae was least abundant in crop fields compared to other study sites. Hesperidae was the least abundant at forest edge (Figure 17).

Figure 17: Butterfly families abundance per habitat

4.3.3 Effect of increasing distance from forest core on butterfly abundance

There was reduction in butterfly abundance between 0.5 – 2 km from the forest core.

However beyond 2 km, the overall butterfly abundance increased remarkably. Increasing distance from forest core to crop fields had no significant effect on butterfly abundance (F1, 4

= 0.439, P = 0.544, R² = 0.099, y = -11.143x + 104.76) (Figure 18).

Figure 18: Effect of distance away from forest core on butterfly abundance

4.4 Cluster analysis of butterfly composition based on Bray-Curtis ecological distance

Crop fields and forest edge shared most of the butterfly species in common compared to fallow farmland and forest core. Butterfly composition in forest core was least similar to that in the crop fields (Figure 19).

Key: X1 – crop field; X2 – Fallow farmland; X3 – forest core; X4 – Forest edge Figure 19: Dendrogram of cluster analysis of butterfly species composition

4.5 Effect of habitat type on the diversity of bees and butterflies

Forest core had the lowest bee diversity (H' = 2.1304). The highest bee diversity was recorded in fallow farmland (H' = 3.0341) then crop fields (H' = 2.9761) while diversity at forest edge was H' = 2.8737 (Figure 20). These diversities were however not statistically significant (F3, 8 = 2.0514, P = 0.1853, n =12). Butterfly diversity was highest at the forest edge, H' = 3.1419. Unlike bee diversity which was lowest in the forest core, butterfly diversity was second highest, H' = 2.7859, fallow farmland had the lowest butterfly diversity where its profile is lowest in the entire range, H' = 2.3640. Crop fields had the second lowest butterfly diversity, H' = 2.5534 (Figure 21).

Key: X1- Crop fields; X2 – Fallow farmland; X3 – Forest core; X4 – Forest edge

Figure 20: Rényi diversity profiles for separate habitats of bee data set

Key: X1- Crop fields; X2 – Fallow farmland; X3 – Forest core; X4 – Forest edge

Figure 21: Rényi diversity profiles for separate habitats for butterfly data set

The difference in butterfly diversity among the study habitats was statistically significant (F3,

8 = 6.329, P = 0.017). Tukey‟s HSD result showed significant difference in butterfly diversity between one pair of the habitats, forest edge and crop fields (P = 0.021), the other pairs were not statistically significant (Table 4).

Table 4: P values for pair wise comparison of butterfly means (Tukey's HSD result at 0.05 level of significance)

Forest core Forest edge Fallow farmland Crop fields

Forest core 1 0.781 0.239 0.104

Forest edge 1 0.057 0.021

Fallow farmland 1 0.962

Crop fields 1

4.5.1 Effect of increasing distance from forest core on bee diversity

Bee diversity was peak between 0.5 km and 1.5 km and reduced gently with increasing distance to crop fields. The diversity was measured using Shannon‟s diversity index (H’). At

1 km, H‟ = 2.6726, at 1.5 from the forest core, H‟=2.6678, at 2 km, H = 2.2998 and 2.5 km,

H‟ = 1.883. The lowest diversity was recorded at 0 km (forest core) which was considered undisturbed area, H‟ = 1.571. Distance away from forest core to crop fields had no significant

2 effect on bee diversity (F1, 4 = 0.0189, P > 0.05, R = 0.0047, y = 0.0341x + 2.243) (Figure

22).

Figure 22: Effect of distance from forest core on bee diversity

4.2.3Effect of increasing distance from forest core on butterfly diversity

Butterflies were more diverse at 0.5 km from the forest core. There was an overall reduction in butterfly diversity with increasing distance from the forest core (Table 5).

Table 5: Butterfly diversity at varying distance from forest core Distance from forest core (km) Butterfly diversity (H’) 0 2.339913 0.5 2.665789 1 1.698388 1.5 1.514743 2 1.692551 2.5 1.548863

However, the reduction in butterfly diversity was not statistically significant (F1, 4 = 6.731, P

= 0.0604, R² = 0.6272, y = -0.4033x + 2.4142) upto 2.5 km from the forest core (Figure 23).

Figure 23: Effect of increasing distance from forest core on butterfly diversity

4.6 Bee relative abundance in the study habitats

Forest core was largely even than other habitats followed by fallow farmlands. Forest edge and crop fields were largely uneven as indicated by their lowest profiles (Figure 24a).

Overall, there was uneven distribution of bee species in the survey area (Figure 24b). The evenness index was J = 0.4271.

(a) (b)

Key: X1-Crop fields, X2-Fallow farmland, X3-Forest core, X4-Forest edge

Figure 24: Rényi evenness profiles of bee data set (a - Rényi profiles for separate habitats; b - overall rènyi profile for the study area)

The high abundance of Ceratina sp.3, Apis mellifera, Xlocopa flavicollis, Braunsapis sp. and

Lipotriches sp.1 largely affected the evenness of bee distribution (Figure 25).

Figure 25: Overall rank-abundance curve showing the most abundant bee species

4.7 Butterfly relative abundance in the study habitats

Forest edge and forest core had largely evenly distributed butterfly community than fallow farmlands and crop fields (Figure 26a). However the overall distribution of butterfly in the survey area was uneven (Figure 26b).

(a) (b) Key: X1-Crop fields, X2 -Fallow farmland, X3-Forest core, X4-Forest edge

Figure 26: Rényi evenness profiles of butterfly data set (a –Rényi profiles for separate habitats; b-Overall rènyi profile forthe study area)

The unevenness was influenced by high abundance of Acraea eponina, Eurema brigitta,

Catopsilia florella, Physcaeneura leda and Bicyclus safitza (Figure 27). The area had an overall evenness index of J = 0.8053 for butterflies.

Figure 27: Overall rank-abundance curve showing the most abundant butterfly species

4.8 Associated floral resources to bees and butterflies

Fourty bee species were linked to their associated floral resources (Table 6).

Table 6: Bee floral resources Bee species Floral resources Amegilla mimadvena Cockerell Hibiscus surattensis Linnaeus Amegilla sp. 1 Vernonia cinerea Less Rhynchosia velutina Wight & Arn Julbernardia magnistipulata Harms Agathisanthemum bojeri Klotzsch Apis mellifera Linnaeus Nesaea radicans Guill. & Perr. Abutilon zanzibaricum Bojer ex Mast Tridax procumbens Linnaeus Sorindeia madagascariensis DC. Ludwigia sp. Julbernardia magnistipulata Harms Agathisanthemum bojeri Klotzsch Braunsapis sp. Paulinia piñata Linnaeus Hoslundia opposita Vahl. Crotalaria emarginata Benth Cocos nucifera Linnaeus

Ceratina sp. 1 Allophylus rubifolius Harms Hoslundia opposita Vahl. Ceratina sp. 2 Tridax procumbens Linnaeus Agathisanthemum bojeri Klotzsch Ceratina sp. 3 Allophylus rubifolius Harms Eriosema glomeratum Guill Gossypioides kiekie Vahl. Paulinia piñata Linnaeus Waltheria indica Linnaeus Ceratina sp. 4 Agathisanthemum bojeri Klotzsch Ceratina sp. 5 Gaultheria indicia Linnaeus Ceratina sp. 6 Agathisanthemum bojeri Klotzsch Ceratina sp. 7 Agathisanthemum bojeri Klotzsch Waltheria indica Linnaeus Dactylurina schmidti Stadelmann Cajanus cajan Linnaeus Urena lobata Linnaeus Euaspis sp. Paulinia piñata Linnaeus Heriades sp. Truimfetta rhomboidea Jacq. Hypotrigona sp. 1 Cajanus cajan Linnaeus Hypotrigona sp. 2 Cajanus cajan Linnaeus Lasioglosum sp. Allophylus rubifolius Harms Eriosema glomeratum Guill. & Perr. Truimfetta rhomboidea Jacq. Lipotriches sp. 1 Pupalia lappacea Linnaeus Lipotriches sp. 2 Pupalia lappacea Linnaeus Lipotriches sp. 3 Agathisanthemum bojeri Klotzsch Lipotriches sp. 4 Hoslundia opposita Vahl. Macrogalea candida Smith Agathisanthemum bojeri Klotzsch Waltheria indica Linnaeus Hewittia malabarica Linnaeus Megachile discolour Smith Crotalaria emarginata Benth Megachile felina Gerstacker Crotalaria emarginata Benth Megachile sp. 2 Indigofera paniculata.Vahl. ex Pers. Indigofera paniculata Vahl. ex Pers. Cajanus cajan Linnaeus Crotalaria emarginata Benth Truimfetta rhomboidea Jacq. Julbernardia magnistipulata Harms Tephrosia villosa Pers. Hyptis suaveolens Poit Megachile sp. 3 Truimfetta rhomboidea Jacq. Hyptis suaveolens Poit Megachile sp. 7 Philenoptera bussei Harms Megachile sp. 8 Hyptis suaveolens Poit Megachille sp. 6 Agathisanthemum bojeri Klotzsch Meliponula ferruginea Lepeletier Cocos nucifera Linnaeus Agathisanthemum bojeri Klotzsch Nomia sp. Julbernardia magnistipulata Harms Pachyanthidium sp. Rhynchosia velutina Wight & Arn. Vernonia cinerea Less Pseudapis sp. Allophylus rubifolius Harms

Eriosema glomeratum Guill. & Perr. Agathisanthemum bojeri Klotzsch Chamaecrista mimosoides Linnaeus Pupalia lappacea Linnaeus Pseudapis sp. 2 Chamaecrista mimosoides Linnaeus Steganomus sp. Crotalaria emarginata Benth Xylocopa caffra Linnaeus Agathisanthemum bojeri Klotzsch Cajanus cajan Linnaeus Xylocopa flavicollis DeGeer Rhynchosia velutina Wight & Arn. Abutilon zanzibaricum Bojer Rhynchosia velutina Wight & Arn. Vernonia cinerea Less Xylocopa hottentota Smith Rhynchosia velutina Wight & Arn Vernonia cinerea Less Waltheria indica Linnaeus Julbernardia magnistipulata Harms Xylocopa nigrita Fabricius Cajanus cajan Linnaeus Xylocopa scioensis Gibodo Rhynchosia velutina Wight & Arn. Vernonia cinerea Less Hyptis suaveolens Poit Crotalaria emarginata Benth Abutilon zanzibaricum Benth

Twenty butterfly species were linked to their floral resources. (Table 7).

Table 7: Butterfly floral resources

Butterfly species Floral resources Acraea acrita Hewitson Aspilia mossambiensis Oliv. Acraea eponina Cramer Emilia coccinea Sims Tridax procumbens Waltheria indica Linnaeus Acraea natalica Boisduval Waltheria indica Linnaeus Acraea satis Ward Tridax procumbens Linnaeus Anthene demarah Guerin-Meve Agathisanthemum bojeri Klotzsch Anthene sp. Agathisanthemum bojeri Klotzsch Azanus natalensis Trimen Vernonia sp. Belenois thysa Hopffer Bridelia cathartica Bertol Waltheria indica Linnaeus

Bicyclus safitza Hewitson Agathisanthemum bojeri Klotzsch Bicyclus sp. Agathisanthemum bojeri Klotzsch Catopsilia florella Fabricius Agathisanthemum bojeri Klotzsch Agerotum conyzoides Linnaeus Lobelia fervens Thunb Sida cordifolia Linnaeus Tridax procumbens Linnaeus Vernonia sp.

Colotis vesta Reiche Pentas bussei Krause Danaus chrysippus Linnaeus Agathisanthemum bojeri Klotzsch Eurema brigitta Stoll Agathisanthemum bojeri Klotzsch

Stylosanthes fruticosa Retz.

Graphium angolanus Goeze Agathisanthemum bojeri Klotzsch Waltheria indica Linnaeus Sida cordifolia Linnaeus

Graphium antheus Cramer Agathisanthemum bojeri Klotzsch Hypolimnas misippus Linnaeus Sida cordifolia Linnaeus Papilio demodocus Brown Catunaregam nilotica Stapf Pardopsis puntatissima Rothschild Kyllinga cartilaginea Schum Physcaeneura leda Drury Asystasia gangetica Linnaeus Hoslundia opposita Vahl. Tridax procumbens Linnaeus

Most bee species were netted while foraging on flowers. However, bees of 10 genera were caught on flight. Two other unidentified bee species were also caught while flying between flowers (Table 8).

Table 8: Bee species caught on flight

Amegilla sp. 2 Amegilla sp. 4 Amegilla sp. 6 Coelioxys sp. Halictus sp. Megachile sp. 5 Pachymelus sp. Thyreus sp. Unidentified 1 Unidentified 2 Xylocopa flavorufa DeGeer Sphecodes sp.

Compared to bee species, most butterfly species were netted on flight (Table 9).

Table 9: Butterfly species caught on flight

Amauris niavius Linnaeus Amauris ochlea Boisduval Appias epaphia Boisduval Appias lasti Grose-Smith Baliochila sp. Bebearia chriemhilda Staudinger Belenois crawshayi Butler Byblia antavara Boisduval Byblia ilithyia Drury Chraxes contrarius Weymer Coenyropsis carcassoni Kielland Colotis antevippe Lucas Colotis euippe Linnaeus

Colotis ione Godart Euphaedra neophron Hopffer Eurema hecabe Butler Euryphura achlys Hopffer Eurytela dryope Cramer Graphium colona Ward Graphium kirbyi Hewitson Hypolimnas anthedon Douleday Hypolimnas usambara Ward Junoia oenone Linnaeus Junonia natalica Felder Leptosia acesta Bernardi Leptotis pirithous Melanitis leda Linnaeus Nepheronia argia Fabricius Nepheronia thalassina Boisduval Neptis goochi Trimen Neptis kiriakoffi Overlaet Neptis saclava Hopffer Papilio dardanus Brown Salamis parhassus Bonte & Van Dyck Spilia sp. Spindasis homeyeri Dewitz Spindasis victoriae Butler Teriomima subpunctata Kirby Tirumala petiverana Klug Ypthima asterope Klug Phalanta phalantha Drury Acraea braeasia Godman

4.8.1 Important floral resources in Muhaka area

Some floral resources were visited by many bee species and were considered important bee flora in the area, e.g. Agathisanthemum bojeri (Plate 6), Crotalaria emarginata, Truimfetta rhomboidea, Cajanus cajan (Plate 7), Rhynchosia velutina, Julbernardia magnistipulata

(Plate 8), Hyptis suaveolens., Eriosema glomeratum and Waltheria indica. However, A. bojeri, Waltheria indica and Vernonia cinerea were important to both bees and butterflies.

Aspilia mossambiensis, Tridax procumbens and Sida cordifolia (Plate 9) were important

specifically to butterfly species.Urena lobata (Plate 10) and Vigna unguiculata (Plate 11)

were also important floral resources in the area.

Plate 6: Xylocopa caffra L. foraging on Agathisanthemum bojeri K.

Plate 7: Cajanus cajan L., a bee pollinated local crop

Plate 8: Jubernardia magnistipulata H., a forest tree pollinated by bees mainly Xlocopa sp.

Plate 9: Graphium angolanus G. foraging on Sida cordifolia L.

Plate 10: Macrogalea candida S. foraging on Urena lobata L. Plate 11: Vigna unguiculata L., a common crop in the area that requires bee pollination.

4.9 Effect of floral resources richness on bee and butterfly species richness

Floral resources richness at sampling points equidistant from the forest core were summed to give the floral resources richness at each distance from the forest core, forming 6 categories of floral resources richness from the 12 sampling points (Table 10).

Table 10: Floral richness and corresponding bee and butterfly species richness

Distance from forest Bee species Butterfly Species Floral resources core (km) richness richness richness 0 11 30 18 0.5 38 43 78 1 30 22 75 1.5 32 16 57 2 28 15 59 2.5 16 14 34

Floral resources richness had significant positive effect on bee species richness (F1, 4 =

36.6443, P = 0.004, R2 = 0.902, y = 0.611x + 1.1448) (Figure 28). However the richness of butterflies was not significantly affected by floral resources richness (F1, 4 = 0.2577, P =

0.638, R2 = 0.061, y= 0.1191x + 16.961).

Figure 28: Effect of floral resources richness on bee species richness

CHAPTER FIVE

DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS

5.1 Effect of habitat type on bee abundance

The overall abundance of bees was high in fallow farmland. Fallow farmland was open with high abundance of flowers. This finding agrees with that of Gikungu et al. (2011) and

Gikungu, 2002; where bee abundance was found to be high in open farmlands. According to

Banaszak (1996) and Potts et al. (2003), the overall bee abundance is a positive function of abundance of flowers in a particular habitat. Agathisanthemum bojeri; a floral resource of rank level 1 (visited by most bee species) was abundant in fallow farmland. In addition,

Waltheria indica which attracted more Ceratina sp. was also abundant.

The type of farming in the region is a non-intensive small scale agriculture where crop fields supported abundant weedy flowering plants after crop harvesting. As a common practice by farmers in the region, these weedy plants are not removed until the next planting season.

During this fallow period they produce flowers which attract bees. The fields are also characterised by unmanaged hedgerows which appear advantageous in allowing the survival of wild flowers which could be a major contributing factor to bee abundance. More open habitats with abundant floral resources will attract abundant foraging bee species, such habitats have greater possibilities for partitioning available resources (Potts et al., 2003), limiting competition between and within species. Open habitats have favourable environmental variables correlated with the abundance of bees including temperature, light intensity and humidity (Liow et al., 2001). Therefore, low bee abundance in the forest could also be caused by low temperatures, higher humidity and low light intensity due to closed forest canopy. Furthermore, only the understory community was surveyed and few understory plants or trees were observed flowering during the sampling period.

Halictidae were more abundant in fallow farmlands compared to other habitats. Possibly fallow farmlands support both annual and perennial plants with high pollen availability relative to nectar that is the crucial property of floral communities that determine the composition of Halictidae (Potts et al., 2003). Stable habitat conditions with grass and shrubs in this habitat could be providing favourable nesting sites for members of this family. Apidae was the dominant bee family across all the study habitats. This compares with the study in

Mt. Carmel where Apidae were found to be dominant (Potts et al., 2003). Most of the members of this family are long distance foragers with advanced foraging behaviour and therefore explore diverse nectariferous flowers across different habitats. They extensively forage for both nectar and pollen across the habitats. Megachilidae were abundant in crop fields. Presence of Papilionaceae plants e.g Cajanus cajan and Crotalaria emarginata could have contributed to its abundance. While Halictidae was linked to pollen rich sites and areas providing good nesting opportunities, Megachilidae appeared to be organized by both nectar and pollen resources. These findings concur with those of Potts et al. (2003) which reported dependence of Megachilidae and Halictidae on pollen rich floral resources in Mt. Carmel.

The findings are evidence that different groups of bees show contrasting responses to land use change, which is probably driven by differences in their foraging and nesting biology

(Brosi et al., 2008).

This study shows that crop fields surrounding KMF can offer supplementary conservation sites for bee species while the forest acts as an ecological restoration site. Habitats are likely to be more effective in enhancing pollinator diversity and abundance when ecological restoration sites are available in the close vicinity (Steffan-Dewenter and Westphal, 2008).

Use of agrochemicals has been found to lower the pollinator diversity and abundance in crop fields (Kremen et al., 2007). No observation was made on agrochemical use in the study area.

This could have contributed to high bee abundance in the crop fields. An ecosystem approach with carefully designed wild flower and crop mixtures in crop fields can be successful in supplying nectar and pollen resources to bee species in farmlands thereby supporting their diversity and abundance in such habitats. Wild flower mixtures in active agricultural landscapes are likely to be most effective supplements or replacements where sources of suitable plant colonists have been eliminated and the vegetation impoverished (Smith et al.,

1994).

5.2 Effect of habitat type on butterfly abundance

Overall butterfly abundance was high in the crop fields followed by fallow farmlands. This could be due to the openness of these habitats. Generalists butterfly species which were netted in relatively higher numbers majorly from the family Nymphalidae could have contributed to the overall abundance in the crop fields. This concurs with Hill et al. (2001) and Schulze et al. (2001) who reported high Nymphalidae abundance in open farmlands.

Farmlands in Kaya Muhaka are characterised by many and scattered cashewnut and mango trees around which are herbaceous plants, seasonal, annual flowering plants and grasslands.

Some parts of the fallow farmland were characterised by open grasslands with stable stands of the highly preferred A. bojeri. Abundant weedy plants after crop harvesting provided floral resources to butterflies in crop fields and fallow farmlands. Despite the fact that these generalists could be less richer than the forest specialists in this region, their numbers could be higher than the forest dependents. This may have lead to the higher abundance in the crop fields. The finding on butterfly abundance also agrees with that of Namu (2005) in which a high butterfly abundance in Kakamega was recorded in a more open habitats compared to the primary forest. It is possible that some modified habitats may support more species of pollinators (Driscoll, 2005).

Two main categories of butterflies in this region are noticed, forest dependent and forest independent. Forest dependent species are contributing to the abundance at the forest and forest edge and forest independent contributing to the abundance in the crop fields and fallow farmlands. According to the findings of this study, 45% of butterfly species recorded in KMF and surrounding farmlands were forest dependent. Some of the forest dependent species recorded were, Hypolimnas usambara, Hypolimnas deceptor, Graphium antheus, Salamis cacta, Neptis goochi, Neptis saclava, Chraxes contrarius, Amauris niavius and Graphium kirbyi. However, Danaus chrysippus, Bicyclus safitza, Catopsilia florella, Acraea eponina,

Eurema hecabe and Eurema brigitta are among the species that showed independence to the forest and high resilience in farmlands.

5.3 Effect of habitat type on bee and butterfly diversity

High bee diversity was recorded in fallow farmlands and crop fields. This was attributed to the richness and abundance of important floral resources in the two habitats. The key floral resources in fallow farmlands and crop fields were largely annuals which supported high bee diversity in the habitats. It is known that bee diversity has a strong positive association with the species richness of annuals (Potts et al., 2003) and overall floral diversity (Banaszak,

1996). Apart from the floral resources richness, fallow farmland showed stable habitat heterogeneity consisting of woody and herbaceous plants which could offer the variety of habitat requirements, including nesting and feeding for diverse bee species. The heterogeneous mix of large cashew nut trees, mango trees and associated woody shrubs, annual flowering plants and grassland patches was probably able to support diverse bee species with diverse foraging behaviour. Crop fields had greater absolute bee species richness. This could be explained by the abundance of floral resources enabling the fields to attract more“wanderer” bee species and those with long foraging ranges, such as Amegilla

52 and Xylocopa sp.. Liow et al. (2001) explains that bees with long foraging ranges are associated to disturbed habitats. The high floral resources richness recorded in fallow farmlands was dominated by more annuals than perennial floral species. The data showed that the difference in bee diversity was not significant among the various habitats. This can be explained by the fact that the habitats were close to each other with a high overlap and probably allowed free movement of bee species. Extensive fallow corridors within the farmlands could have contributed to greater habitat overlap leading to the closeness in bee species diversity among the habitats. However, bee species composition at the forest edge was closely similar to that in crop fields. This can be explained by a possible similarity in floral resource composition and richness between the two habitats.

High butterfly diversity and absolute species richness were recorded at forest edge and forest core. The habitat heterogeneity at the forest edge could be effective in offering habitat requirements for both adult butterflies and their developmental stages. High floral resources abundance in this habitat could have also contributed to the high butterfly diversity. A positive reletionship is known to exist between butterfly diversity and floral abundance

(Steffan-Dewenter and Tscharntke, 1997). Butterfly diversity was significantly higher at the forest edge than crop fields. This shows that a greater proportion of butterfly species of Kaya

Muhaka could be restricted to the forest and forest edge with limited foraging ranges between the two habitats. Probably, the forest and forest edge provide specific habitat requirements for diverse butterfly species in the area. Butterflies are known to exhibit specific habitat requirements, namely adequate numbers of a single or a few host-plants for oviposition, nectar-source plants, or even more cryptic resources ranging from mutualistic dependencies to pools of standing water for critical minerals (Baz and Antonio, 1995). Many of these butterflies in the forest could be specialised to inhabit the forest understorey and feed on

53 other food sources other than flowers. The food resources could be restricted in the forest and within the narrow range of forest core and forest edge. This concept highlights the significance of the forest in the conservation of butterflies.

Maybe some species can only thrive within the microclimate provided by closed canopies of the forest. It could be justified to acertain that the presence of this forest is key to support of diverse butterfly species in the area. Crop fields had the lowest butterfly diversity compared to the other habitats. This could mean that the area consists of few generalist butterfly species which have long foraging ranges and are associated with disturbed habitats, habitat disturbance favours generalist butterfly species irrespective of habitat distinctiveness

(Spintzer et al., 1993) and can be found in areas altered by humans (Davros et al., 2006). The close similarity in butterfly species composition between forest edge and crop fields could mean that most butterfly species found at the forest edge had long foraging ranges and were able to utilize floral resources in crop fields and forest edge. It could also mean that the two habitats had closely similar habitat composition leading to inhabitation by closely similar butterfly species. Forest core showed least similarity in butterfly composition to crop fields.

This can be explained by the presence of two categories of butterflies in the area, forest dependent and forest independent. Forest indipendents inhabited majorly open farmlands with some having extensive foraging ranges from forest edge to crop fields. The forest dependents were restricted to KMF and its edge. Forest dependents are habitat sensitive and have more specific requirements for habitat and vegetation composition to suit the needs of their developmental life stages and are often found only in relatively natural areas with native vegetation (Steffan-Dewenter and Tscharntke, 1997) like in the case of KMF. This highlights further the need to conserve the forest.

5.4 Effect of increasing distance from forest core on bees and butterflies

Distance away from the forest core had no significant effect on overall butterfly abundance and diversity. Increasing distance from forest core also had no significant effect on bee species richness, diversity and abundance. The findings conform to the pattern found by

Klein et al. (2007) and Banaszak (1992) which reported no change in bee diversity or abundance with distance from the forest. It also agrees with the findings of a similar research done at Las Cruces forest in southern Costa Rica in which overall bee abundance, species richness, and diversity did not vary significantly with distance from a large forest fragment

(Brosi et al., 2007). Bee communities appear to have some degree of resilience to land use change. Bee and butterfly species showed resilience to human settlement, unplanned multiple access routes and continuous vegetation clearance around settlements for perpetual monocroping and related activities. The levels of these activities were not intense in the region. This could have contributed to the persistence of bee and butterfly populations even in points away from the forest. There is need to control these activities to avoid reaching threat levels. The overall bee abundance, absolute species richness and diversity did not vary significantly with distance from the forest. This implies that most bees are rather dependent on habitat quality than proximity to primary forests.

The Kaya forest and forest edge probably acts as abuffers for the conservation of bees and butterflies where they seek refuge for nesting and foraging when the farmlands are extensively impoverished and indiscriminately disturbed. A. bojeri, a priority floral resource to both bee and butterflies was dominant upto 1 km from the forest. This could have also contributed to the reduction of abundance and diversity of the bee species. Though the level of habitat heterogeneity in the habitats was not the same, it was realised across all the habitats. This could have been the most important factor that influenced the diversity and

55 abundance of bees. Regional habitat heterogeneity could be more important factor than farming practice in influencing the diversity and abundance of pollinators in agricultural landscapes (Brosi et al., 2008). However, there was significant reduction in diversity of butterflies with increasing distance from forest core. This implies a high butterfly diversity in forest edge and forest core while farmlands (Crop fields and fallow farmland) recorded a low butterfly diversity. Forest specialists are sensitive to habitat disturbance highlighting further the role of Kaya forest in the conservation of butterflies in the region. The loss of this primary forest would mean loss of these forest specialists. Butterfly families, Nymphalidae and

Pieridae were more resilient to habitat disturbance and distance from the forest. The two families have strong powers of flight and open population structures such that they are unlikely to be constrained by a lack of shelter, thus allowing them to exploit resources inaccessible to other less vagile species (Dover, 1996) like those of family Hesperiidae. It is possible that most members of the two butterfly families are generalist species which are able to utilize a wide range of floral resources across the habitats including disturbed areas. The opportunist butterflies with wide geographic distribution, most of them migrants, are associated with disturbed habitat (Spitzer et al., 1993).

5.5 Effect of habitat type on bee and butterfly relative abundance

All the habitats recorded low relative abundance for both bees and butterflies. The relative abundance of pollinators in a habitat is dependent on the distribution and abundance of floral resources. This could mean that floral resources in the study area were patchily distributed, less diverse and were not in abundance throughout the habitats to support high proportions of individual bee and butterfly populations. The low abundance of some bee species especially solitary bees could be attributed to low numbers or absence of their preferred host plants.

Probably the sampling period did not coincide with the emergence of some bee species as

56 well as the blooming time of their floral resources. Therefore, the associated bee species were recorded in relatively low numbers leading to the low relative abundance. According to

Minckley et al. (2000) the emergence of certain solitary bees is governed by the blooming time of their host plants and the distribution of their host plants directly influence their distribution.

The principal determinants of relative abundance of pollinator species is closely linked to quality of forage resources, habitat heterogeneity, impact of natural enemies and plant structural diversity (Potts et al., 2003).

Bees and butterfly utilization of these resources in the area could be a matter of chance. It could also mean that the floral resources were restricted to certain parts of the habitats restricting high densities of these pollinators in such areas during the flowering season. It is known that the niche space of butterflies (i.e., the amount of their resources) strongly influences the abundance of butterflies and consequently butterfly biodiversity patterns

(Yamamoto et al., 2007) and relative abundance. On the other hand bees are completely dependent on flowers for food, their distribution pattern is therefore closely linked to the distribution pattern of their floral resources. This finding points to a possible limitation of floral resources to the local bees and butterflies. The findings also imply that while some butterfly and bee species are abundant in Kaya Muhaka some could be rare.

5.6 Effect of floral resources on bees and butterflies

Most of the bee species were generalized feeders and visited many of the floral resources.

The bee species visited more than one plant species. This finding agrees with that of Waser et al. (1996) in which plant-pollinator interactions was found to be generalized. They found that in many cases a single plant species was visited by more than one bee species and one bee species visited more than one plant species. There was a positive correlation between floral resources

57 richness and bee species richness. A similar result was found by Potts et al. (2003) and Banaszak

(2000). It was possible to link most of the bee species collected to their associated floral resources unlike butterfly species. This is because most bees were collected as they were foraging except afew, while most butterflies were collected on flight. This shows that bees unlike butterflies are completely dependent on flowers for their food requirements (Neff and Simpson, 1993) and their diversity within a habitat is linked to the diversity of flowering plants (Banaszak, 2000).

Their population structure is highly dependent on the composition of the plant community that provide the resources. This is emphasized by Samways and Wright (1998) in which gall-insect species richness was found to be highly dependent on plant richness.

The general pattern of floral resources utilization by bees and butterflies and habitat selection with respect to suitable flowers seems to be that of opportunistic use of what is available through the season, which is certainly advantageous under unpredictable conditions. The observed lack of correlation between butterfly species richness and floral richness of the study area conforms to the observation that overall butterfly diversity at a site is more influenced by the diversity of nearby vegetation types than by the local plant diversity of the site itself (Sharp et al., 1974). Most butterflies in this region could also be depending on other food resources other than flowers and only a few are over-dependent on flowers. The influence of plant associations on butterfly distribution seems to be one of scale. The range of the animals, the distribution of particular plants of critical importance to them, and the predictability of their environment all play a part in determining what the pattern of habitat selection will be for each butterfly population (Sharp et al., 1974).

5.7 Conclusions

i. Habitat heterogeneity could be a more important factor influencing the diversity and

abundance of bees and butterflies. Sites with high heterogeneity have the highest

capacity to satisfy the diverse ecological requirements of insect pollinators including

shelter, foraging, mating and breeding sites. Heterogenous habitats support high bee

diversity and an overall pollinator abundance.

ii. Forest core, forest edge, fallow farmlands and crop fields are all important in the

conservation of bees and butterflies and complement each other in the conservation of

the species. However, some butterfly species are forest dependents. At least 45% of

butterfly species recorded during the study were seen to have preference to forest and

forest edge, pointing towards the need to conserve the forest.

5.8 Recommendations

i. There is need to focus on conservation of insect pollinators in the coastal region

through an integrated approach e.g. community based projects on bee keeping and

butterfly farming.

ii. Ecosystem approach to farming and careful planning of farmlands with wildflowers

and crop mixtures to improve habitat quality and heterogeneity to sustain bee and

butterfly populations.

iii. There is need for further studies on habitat preference, species rarity and spatial

distribution of bee and butterfly communities in the study area and other coastal

forests.

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Appendix I: Checklist of bee species in KMF and surrounding farmlands Bee species Sampling points A1 A2 A3 A4 A5 A6 B1 B2 B3 B4 B5 B6 Amegilla mimadvena Cockerell 0 0  0  0 0 0 0 0  0 Amegilla sp. 1 0        0  0 0 Amegilla sp. 2 0 0 0 0 0  0 0 0 0  0 Amegilla sp. 4 0  0 0 0 0 0 0 0  0 0 Amegilla sp. 6 0   0 0 0 0 0 0 0 0 0 Apis mellifera Linnaeus 0          0  Braunsapis sp. 0   0  0 0    0 0 Ceratina sp. 1 0  0  0     0  0 Ceratina sp. 2 0  0  0 0 0 0 0  0  Ceratina sp. 3             Ceratina sp. 4 0  0    0  0 0   Ceratina sp. 5 0 0 0  0 0 0 0 0 0 0 0 Ceratina sp. 6 0 0 0  0 0 0   0 0 0 Ceratina sp. 7 0  0 0   0   0  0 Coelioxys sp. 0 0 0 0 0 0 0 0 0  0 0 Dactylurina schmidti Stadelmann 0 0 0   0 0 0   0 0 Euaspis sp. 0  0 0 0 0 0 0 0 0 0 0 Halictus sp. 0 0 0 0 0 0 0 0 0  0 0 Heriades sp.  0  0  0 0    0 0 Hypotrigona sp. 1 0 0 0   0 0    0 0 Hypotrigona sp. 2 0 0 0 0 0 0 0  0 0 0 0 Lasioglosum sp. 0 0 0 0 0 0    0 0 0 Lipotriches sp. 1 0      0    0 0 Lipotriches sp. 2 0   0 0 0 0 0 0 0 0 0 Lipotriches sp. 3 0  0  0 0 0 0    0 Lipotriches sp. 4 0 0  0 0 0 0 0  0 0 0 Macrogalea candida Smith 0   0   0     0 Megachile discolour Smith 0 0 0  0 0 0 0  0 0 0 Megachile feline Gerstacker 0 0 0 0  0 0 0   0 0 Megachile sp. 2 0       0    0 Megachile sp. 3 0  0  0 0 0 0   0 0 Megachile sp. 5 0 0 0 0  0 0 0 0 0 0 0 Megachile sp. 7  0 0  0 0 0 0 0 0 0 0 Megachile sp. 8 0  0 0 0 0 0 0   0 0 Megachille sp. 6 0 0 0 0 0 0 0  0 0 0 0 Meliponula ferruginea Lepeletier 0 0  0 0 0 0 0   0 0 Nomia sp. 0  0 0 0 0  0 0 0 0 0 Pachyanthidium sp. 0  0 0 0  0 0 0 0 0 0 Pachymelus sp. 0 0 0 0  0 0 0 0 0 0 0 Pseudapis sp. 0     0     0  Pseudapis sp. 2 0  0 0 0 0 0 0   0 0 Sphecodes sp. 0  0 0 0 0 0 0 0 0 0 0 Steganomus sp. 0  0 0 0 0 0 0   0 0 Thyreus sp. 0 0 0 0  0 0 0 0 0 0 0 Unidentified 1 0 0 0 0 0  0  0 0 0 0 Unidentified 2 0 0 0 0  0 0  0 0 0 0 Xylocopa caffra Linnaeus 0     0 0     0 Xylocopa flavicollis DeGeer 0   0  0 0   0 0  Xylocopa flavorufa DeGeer 0 0 0 0 0 0 0 0 0  0 0 Xylocopa hottentota Smith   0 0 0 0   0 0  0 Xylocopa nigrita Fabricius 0  0 0 0 0 0  0  0 0 Xylocopa scioensis Gibodo 0   0 0  0 0    0

Appendix II: Checklist of butterfly species in KMF and surrounding farmlands

Butterfly species Sampling points A1 A2 A3 A4 A5 A6 B1 B2 B3 B4 B5 B6 Acraea acrita Hewitson 0 0 0 0 0  0 0 0  0 0 Acraea braeasia Godman 0   0 0 0 0 0 0 0 0 0 Acraea eponina Cramer   0    0   0 0 0 Acraea natalica Boisduval 0 0 0  0 0 0   0 0 0 Acraea satis Ward  0 0 0 0 0  0 0 0 0 0 Amauris niavius Linnaeus  0 0 0 0 0   0 0 0 0 Amauris ochlea Boisduval 0  0 0  0  0 0 0 0  Anthene demarah Guerin-Meve 0 0 0 0 0 0 0  0 0 0 0 Anthene sp. 0  0 0 0 0 0 0 0 0 0 0 Appias epaphia Boisduval 0 0 0 0 0 0  0 0 0 0 0 Appis lasti Grose-Smith 0 0 0 0 0 0  0 0 0 0 0 Azanus natalensis Trimen 0 0 0 0 0 0 0  0 0 0 0 Baliochila sp. 0 0 0 0 0 0  0 0 0 0 0 Bebearia chriemhilda Staudinger 0 0 0 0  0 0 0 0 0 0 0 Belenois crawshayi Butler 0 0 0 0 0 0 0 0  0  0 Belenois creona Cramer 0 0 0 0  0 0 0 0 0 0 0 Belenois thysa Hopffer 0 0 0 0 0 0 0  0   0 Bicyclus safitza Hewitson 0  0 0 0 0   0 0   Bicyclus sp. 0 0 0 0 0  0 0 0 0 0 0 Byblia antavara Boisduval 0 0 0 0  0 0  0 0 0 0 Byblia ilithyia Drury 0 0 0 0 0 0 0 0 0 0  0 Catopsilia florella Fabricius 0 0 0  0 0 0  0  0  Chraxes contrarius Weymer 0 0 0 0 0 0 0  0 0 0 0 Coenyropsis carcassoni Kielland 0 0 0 0 0 0 0 0  0 0 0 Colotis antevippe Lucas 0 0 0 0 0  0 0 0 0  0 Colotis euippe Linnaeus 0 0 0 0 0  0 0 0 0 0 0 Colotis ione Godart 0 0  0 0 0 0 0 0 0 0 0 Colotis vesta Reiche 0  0 0 0 0 0 0 0 0 0 0 Danaus chrysippus Linnaeus 0 0 0 0  0 0 0  0 0 0 Euphaedra neophron Hopffer 0  0 0 0 0   0 0  0 Eurema brigitta Stoll 0   0 0    0  0 0 Eurema hecabe Butler 0 0 0 0 0 0 0  0 0 0  Euryphura achlys Hopffer 0 0 0 0 0 0   0 0 0 0 Eurytela dryope Cramer  0 0 0 0 0 0 0 0 0 0  Graphium angolanus Goeze 0   0 0 0 0   0 0 0 Graphium antheus Cramer 0  0 0 0 0 0 0 0 0 0 0 Graphium colona Ward   0 0 0 0 0 0  0 0 0 Graphium kirbyi Hewitson  0 0 0 0 0 0 0 0 0 0 0 Hypolimnas anthedon Douleday 0 0 0 0 0 0  0 0 0 0 0 Hypolimnas deceptor Trimen  0 0 0 0 0 0 0 0 0 0 0 Hypolimnas misippus Linnaeus  0 0 0 0 0 0    0 0 Hypolimnas usambara Ward 0 0 0 0 0 0 0  0 0 0 0 Junonia natalica Felder 0   0 0 0 0  0 0 0 0 Junonia oenone Linnaeus 0  0 0 0 0 0 0 0    Leptosia acesta Bernardi  0 0 0 0 0 0  0 0 0 0 Leptotes pirithous Linnaeus 0  0 0 0 0 0 0 0  0 0 Melanitis leda Linnaeus 0 0 0 0 0 0 0 0  0 0 0 Nepheronia argia Fabricius 0 0 0 0 0 0  0 0 0 0 0 Nepheronia thalassina Boisduval 0 0 0 0 0 0  0 0 0 0 0 Neptis goochi Trimen  0 0 0 0 0  0 0 0 0 0 Neptis kiriakoffi Overlaet 0  0 0 0 0 0 0  0 0 0 Neptis saclava Hopffer  0 0 0 0 0  0 0 0 0 0

Papilio dardanus Brown 0 0 0 0 0 0 0 0 0 0  0 Papilio demodocus Esper 0  0 0 0 0 0 0   0 0 Pardopsis puntatissiman Rothschild 0 0 0 0 0 0 0 0 0  0 0 Phalanta phalantha Drury   0  0 0 0  0 0 0 0 Physcaeneura leda Drury 0    0  0   0 0 0 Pseudacraea lucretia Cramer 0 0 0 0 0 0 0  0 0 0 0 Salamis cacti Fabricus 0 0 0 0 0 0   0 0 0 0 Salamis parhassus Bonte & Van Dyck 0 0 0  0 0  0 0 0 0 0 Spilia sp. 0 0 0 0 0 0 0  0 0 0 0 Spindasis homeyeri Dewitz 0 0  0 0 0 0 0 0 0 0 0 Spindasis victoria Butler 0 0 0 0 0 0 0 0  0 0 0 Teriomima subpunctata Kirby 0 0 0 0 0 0 0 0 0 0  0 Tirumala petiverana Klug 0 0 0 0 0  0 0 0  0 0 Ypthima asterope Klug 0 0  0 0 0 0  0 0 0 0

Appendix III: General list of floral resources in KMF and surrounding farmlands

Family Floral resources Papilionaceae Abutilon zanzibaricum Bojer ex Mast. Rubiaceae Agathisanthemum bojeri Klotzsch Compositae Ageratum conyzoides Linnaeus Sapindaceae Allophylus rubifolius Harms Compositae Aspilia mossambiensis Oliv. Acanthaceae Asystasia gangetica Linnaeus Euphorbiaceae Bridelia cathartica Bertol Papilionaceae Cajanus cajan Linnaeus Rubiaceae Catunaregam nilotica Stapf Caesalpiniaceae Chamaecrista mimosoides Linnaeus Palmae Cocos nucifera Linnaeus Papilionaceae Crotalaria emarginata Benth Compositae Emilia coccinea Sims Papilionaceae Eriosema glomeratum Guill. & Perr. Malvaceae Gossypioides kirkii Vahl. Convolvulaceae Hewittia malabarica Linnaeus Malvaceae Hibiscus surattensis Linnaeus Labiatae Hoslundia opposita Vahl. Labiatae Hyptis suaveolens Poit Papilionaceae Indigofera paniculata Poit Caesalpiniaceae Julbernardia magnistipulata Harms Cyperaceae Kyllinga cartilaginea Schum Lobeliacea Lobelia fervens Thunb Onagraceae Ludwigia sp. Lythraceae Nesaea radicans Guill. & Perr. Sapindaceae Paulinia piñata Linnaeus Rubiaceae Pentas bussei Krause Fabaceae Philenoptera bussei (Harms) Schrire Amaranthaceae Pupalia lappacea Linnaeus Papilionaceae Rhynchosia velutina Wight & Arn. Malvaceae Sida cordifolia Linnaeus Anacardiaceae Sorindeia madagascariensis DC. Papilionaceae Stylosanthes fruticosa Retz. Papilionaceae Tephrosia villosa Linnaeus Compositae Tridax procumbens Linnaeus Tiliceae Truimfetta rhomboidea Jacq. Malvaceae Urena lobata Linnaeus Compositae Vernonia cinerea Less. Compositae Vernonia sp. Sterculiaceae Waltheria indica Linnaeus

Appendix IV: Floral resources preference by bee species

Floral resource Number of visiting bee species Agathisanthemum bojeri Klotzsch 14 Crotalaria emarginata Benth 7 Waltheria indica Linnaeus 7 Truimfetta rhomboidea Jacq. 6 Allophylus rubifolius Harms 5 Julbernardia magnistipulata Harms 5 Rhynchosia velutina Wight & Arn. 5 Vernonia cinerea Less 5 Cajanus cajan Linnaeus 4 Eriosema glomeratum Guill. & Perr. 4 Hyptis suaveolens Poit 4 Abutilon zanzibaricum Bojer ex Mast. 3 Hoslundia opposite Vahl. 3 Paulinia piñata Linnaeus 3 Pupalia lappacea Linnaeus 3 Chamaecrista mimosoides Trimen 2 Cocos nucifera Linnaeus 2 Tridax procumbens Linnaeus 2 Gossypioides kirkii Vahl. 1 Hewittia malabarica Linnaeus 1 Hibiscus surattensis Linnaeus 1 Indigofera paniculata Poit 1 Ludwigia sp. 1 Nesaea radicans Guill. & Perr. 1 Philenoptera bussei Harms 1 Sorindeia madagascariensis DC. 1 Tephrosia villosa Linnaeus 1

Appendix V: Distance matrix calculated using bray-curtis

Distance matrix for butterfly data set

X1 X2 X3 X2 0.6908517 X3 0.8704453 0.9230769 X4 0.5816993 0.6382253 0.8116592

Distance matrix for bee data set

X1 X2 X3 X2 0.4000000 X3 0.7132616 0.7396825 X4 0.3545455 0.4243697 0.6679245

Key: X1- Crop fields, X2 - Fallow farmland, X3 - Forest core, X4 - Forest edge

Appendix VI: Some common bee species collected in Muhaka, Kwale Kenya

Amegilla sp. Apis mellifera Linnaeus

Megachile felina Gerstacker Xylocopa flavicollis DeGeer

Xylocopa nigrita Fabricius Ceratina sp.

Megachile sp. Megachile discolor Smith

Appendix VII: Some forest dependent butterfly species in Kaya Muhaka forest

Hypolimnas usambara Ward Hypolimnas usambara Ward (Back side) (Under side)

Hypolimnas anthedon Douleday Salamis parhassus Bonte & Van Dyck

Euphaedra neophron Hopffer

Appendix VIII: Bee taxonomy certificate