BINDURA UNIVERSITY OF SCIENCE EDUCATION

DEPARTMENT OF NATURAL RESOURCES

THE INFLUENCE OF HABITATS ON THE DIVERSITY OF

BY

CHIKUTSA TAFADZWA

(B1336698)

A PROJECT SUBMITTED IN PARTIAL FULLFILLMENT OF THE REQUIREMENTS OF THE BACHELOR OF SCIENCE HONOURS DEGREE IN NATURAL RESOURCES MANAGEMENT

MARCH 2017

DEDICATION ‘This project is dedicated to the Lord Almighty and the entire Chikutsa family’

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ACKNOWLEDGEMENTS I would like to express my sincere gratitude to my academic supervisors Dr. J Muvengwi and Professor G Nyamadzawo for their endless support, advice from the designing of the project topic, data collection and time to correct this manuscript up to its final documentation of this project. I am also grateful to the Bindura University Laboratory technician for assistance during species identification as well as Miss M Mbiba for her great help during data presentation. Appreciation is extended to Honorable Matangira and the Fullers Asssggregate manager for granting me permission to carry out this study in their respective areas.

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ABSRACT A study on the influence of habitats on the diversity of ants across three sites (Miombo woodland, Acacia plantation and maize agricultural field) in the Bindura district was carried out. Precisely the objective of the study was to determine if habitats have an effect on abundance as well as ant species richness. The study had baiting (using 5 determinants –sugar, jam, peanut butter, tuna and honey) and hand collecting being used to collect the ants over a 5 hour period on each site before being stored in 70% alcohol for preservation and later identification at the laboratory. A total of 827 ants and 9 species were collected with higher diversity recorded in the Miombo woodland compared to the Acacia woodland and the agricultural field and it was concluded that habitats shave an effect on the diversity of ants.

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LIST OF FIGURES Fig 3.1: Map showing location of the study area 10

FIG 3.2: Diagram showing sampling points 12

FIG 4.1 a: Proportional functional abundance across the three sites 14

FIG 4.1b: Proportional bait abundance across the three sites 14

FIG 4.2a: Bait richness across the three sites 14

FIG 4.2b: Functional richness across the three sites 14

FIG 4.3: Non metric multidimensional scaling (NMDS) ordination of the Miombo woodland,

Acacia woodland and the Agricultural field. 15

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LIST OF TABLES Table 4.1: Ant species collected at the study sites 13

Table 4.2: Shannon diversity index across the study sites 13

Table 4.3: Rstatistic comparison over the study sites 13

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LIST OF ACRONYMS AND ABBREVIATIONS pH Potential of Hydrogen P Phosphorus K Potassium N Nitrogen CA Calcium NMDS Non Multidimensional scaling

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Table of Contents DEDICATION ...... i ACKNOWLEDGEMENTS ...... ii ABSRACT ...... iii LIST OF FIGURES ...... iv LIST OF TABLES ...... v LIST OF ACRONYMS AND ABBREVIATIONS ...... vi CHAPTER 1 ...... 1 INTRODUCTION ...... 1 1.1 BACKGROUND ...... 1 1.2 PROBLEM STATEMENT ...... 2 1.3 JUSTIFICATION ...... 2 1.4 AIM ...... 3 1.5 OBJECTIVES ...... 3 1.6 RESEARCH HYPOTHESIS...... 3 1.7 ASSUMPTIONS ...... 3 CHAPTER 2 ...... 4 LITERATURE REVIEW ...... 4 2.1 ANTS ...... 4 2.2 ANTS AS SOIL ENGINEERS ...... 4 2.2.1PHYSICAL CHANGE ...... 4 2.2.3 CHEMICAL CHANGES ...... 5 2.2.4NUTRIENT AND ENERGY FLUXES CHANGES ...... 5 2.2.5 ANTS AND VEGETATION ...... 5 2.3 SPECIES DIVERSITY ...... 5 2.4 ANTS AND ENVIROMENTAL GRADIENTS ...... 6 2.4.1ALTITUDE ...... 6 2.4.2VEGETATION/SOIL ...... 6 2.4.3 LANDSCAPE AND SEASONALITY ...... 6 2.4.4TEMPERATURE ...... 7

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2.4.5 LATITUDE AND RAINFALL ...... 7 2.5 ANT DIVERSITY AND DISTURBANCE GRADIENTS ...... 7 2.5.1ROAD CONSTRUCTION ...... 7 2.5.2FIRE...... 7 2.5.3 AGRICULTURE ...... 8 2.5.4 DEFORESTATION ...... 8 CHAPTER 3 ...... 9 RESULTS ...... Error! Bookmark not defined. 3.1 STUDY AREA ...... 10 3.2 DATA COLLECTION ...... 10 3.3 ANTS IDENTIFICATION ...... 11 3.4 DATA ANALYSIS ...... 11 CHAPTER 4 ...... 13 4.1RESULTS ...... 13 4.2 DIVERSITY ...... 13 4.3 ANT ABUNDANCE ...... 13 4.4 SPECIES RICHNESS ...... 14 4.5 SIMILARITY ANALYSES ...... 15 CHAPTER 5 ...... 16 DISCUSSION ...... 16 5.1 SPECIES DIVERSITY ...... 16 5.2 ANT ABUNDANCE ...... 16 5.3 SPECIES RICHNESS ...... 17 5.4 NMDS DISPLAY PATTERNS ...... 17 5.5 LIMITATIONS TO THIS STUDY ...... 17 CHAPTER 6 ...... 18 CONCLUSION AND RECOMMENDATION ...... 18 6.1 CONCLUSION ...... 18 6.2 RECOMMENDATIONS ...... 18 6.2.1FUTURE STUDIES ...... 18 6.2.2 MANAGEMENT ...... 18 REFERENCES ...... 18

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APPENDICES ...... 24 APPENDIX 1 ...... 24 APPENDIX 2 ...... 24 APPENDIX 3 ...... 25

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CHAPTER 1

INTRODUCTION 1.1 BACKGROUND The world is experiencing biodiversity loss at an alarming rate (Díaz et al , 2006) and a lot of effort is being put to understand the drivers of biodiversity loss. Biodiversity despite being one of the pivotal topics of the Rio conference in the 1990’s, little attention has been centered on the conservation of soil communities in subtropical savanna (Raustiala and The Biodiversity Problem, 2004). At large spatial scale the diversity of macro fauna is determined by factors such as climate, landscape structure and vegetation cover (Dauber et al , 2003). Habitat alteration by fire, drought and agriculture has serious consequences on the structure and functioning of ecosystems (Saunders et al , 2007). In the tropics, agriculture and plantation forestry have been observed to be top activities negatively impacting flora and fauna diversity (Barlow et al , 2007). Macroinvertebrates are known to respond to variability in habitat heterogeneity and disturbance (McIntyre et al, 2001), that makes them good indicator species and key biodiversity conservation and monitoring for example, ants and termites are some of the widely distributed macro invertebrates (Chen et al , 2014) that can be used for conservation monitoring in tropical and sub tropical savanna. Although the diversity of ants has been looked at along disturbance gradients such as fire (Vasconcelos et al , 2016; Vaunderwoude and Andersen, 1997), rainfall (Andersen et al , 2015) and soil fertility (Deblauwe and Dekoninck, 2007), little is known on the effect of different habitats on the diversity of ants in savannas.

Ants (Order: ) contribute a great part of the biomass and act as ecosystem engineers in the ecosystems where they occur (Folgarait, 1998). Ants play important roles in the ecosystem that include nutrient cycling through burying organic matter in the soil (Paysen, 2007) as well as improving water infiltration from tunneling activities during nest and runway construction (Kendrick et al , 2015). Most ants facilitate seed dispersal as they carry seed below ground during foraging (Yanoviak et al , 2000). Furthermore, nests that are built by ants act as sources of ecosystem heterogeneity through soil nutrient concentration when they move soil particles rich in clay from deeper horizons (Jilkova and Frouz, 2010). These ant hills support diverse vegetation as compared to the surrounding savanna matrix.

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Habitat loss is one of the major causes of local and global biodiversity loss (Ceballos et el , 2010). Habitat loss is usually caused by natural fires floods drought and agricultural activities. Plantation forestry has been observed to be among the main contributors to the decline of ant species as they increase chances of colonization by invasive ant species (ZamoranoElgueta et al , 2015). However, agricultural expansion has been observed to be one of the worst landuses that compromise diversity (Barlow et al , 2007). Little has been done in subtropical savanna to understand the effect of agriculture and other pure stands of natural woodlands on the diversity of ants.

These studies show a change in the diversity of ants however a question still remains unanswered; is it the land use or the practice under which these activities are being done?. Nearly all studies carried out find clear changes in ant species composition in modified habitats compared with nearby natural areas (Uno et al ,2010) hence the need of a comparative research between monoculture natural woodlands and an agricultural field given the variation of results along many environmental gradients in the savanna region.

1.2 PROBLEM STATEMENT An indefinite quantity of arthropod species are disappearing from ecosystems undetected despite their vital role in sustaining productivity and biodiversity in tropical savannas. Loss of native habitats through activities such as agriculture and the effect of other pure stands of natural woodlands such as acacia on ant diversity are poorly understood.

1.3 JUSTIFICATION

Ants are well known among the most significant soil engineers (Folgarait 1998) and of late changes in ant species composition in modified habitats compared to nearby natural areas have been observed (Uno et al , 2010) and this has a negative effect on ecosystem functioning. This study on the effect of different monoculture habitats on ant diversity is important in the conservation and management of the species. Studies on the effect of plantations (Thongphak, 2014) and agriculture (Uno et al , 2010) have been done elsewhere, and little is known for sub tropical savanna woodlands, especially natural pure stands. The findings of this study will add value to the conservation of ants ( at large) in their natural ecosystems.

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1.4 AIM To assess the effect of agriculture and related pure stands of natural vegetation resembling monoculture on ant diversity.

1.5 OBJECTIVE

To determine the effect of habitat on ant diversity

1.6 RESEARCH HYPOTHESIS

Variation in habitats has an effect on ant diversity

1.7 ASSUMPTIONS Soil type and pH of the three sites is assumed to be the same

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CHAPTER 2

LITERATURE REVIEW 2.1 ANTS Ants are among the most collectively recognized and widely studied groups (Marques and DelClaro, 2006). They are classified in a solitary family Formicidae within the order Hymenoptera (Sharaf et al , 2012) and these families are further divided into 21 subfamilies. Ants like all have a hard exoskeleton which defends the soft interior, their body is divided into 3 parts namely head, thorax and abdomen (McGrawHill 2004) and differ in size from less than 2 millimeters to over 248(Sharaf et al, 2012).They are helometabolous insects which undergo complete metamorphism meaning that they pass through four different life stages thus egg, pupa, larvae and adult (SpicerRice 2013). They are social insects since they live in large cooperative family groups called castes that execute different functions namely the queen, male and (female) workers (McGrawHill 2004).

2.2 ANTS AS SOIL ENGINEERS Ants are acknowledged among the most vital soil engineers (Folgarait 1998) meaning that they indirectly modulate the accessibility of resources to other species by causing physical and chemical state fluctuations in biotic and abiotic materials (Gkisakis et al 2015). Ant subjective soil environment affects the activity and abundance of other soil biota such as microorganisms and soil insects (Frouz and Jilková, 2008).

2.2.1 PHYSICAL CHANGE This is related to the soil profile were soil properties are altered by ants (Frouz and Jilková, 2008). Ants when abundant modify the soil structure through the formation of gallery and chamber systems during transportation of their food, soil materials and feeding (Chen et al , 2014). During this process known as bioturbation there is the mixing and accumulation soil from different sources and horizons (Kendrick et al, 2015). Galleries and tunnels are dug before being colonized by ants while the smaller particles are moved to the surface and the compacted materials broken down as well as organic materials are taken below the surface (Paysen 2007). The network of galleries and chambers increases soil porosity, aeration, infiltration and drainage in that way creating habitats for smaller organisms (Chen et al , 2014) as well as decreasing bulk density (Paysen 2007). Temperature is another physical factor that is altered by ants especially

4 regulation of internal temperatures which has been observed for nests with ant hills (Marques and DelClaro, 2006).

2.2.3 CHEMICAL CHANGES Ants also impact chemical changes in the soil although these differ with soil characteristics or ant species involved (Folgarait 1998).Chemical modifications are linked with the organic remains of plants and that are brought into the nest where they subsequently decompose and become mixed with mineral elements (Yanoviak et al , 2000). These activities influence the soil chemistry by increasing the amounts of organic matter P, K, N in mounds and they lower pH in alkaline soils and increase pH in acidic soils (Folgarait 1998). A study by( Jilkova and Frouz , 2010) showed that with space from the ant nest there was a change in pH as well as Ca, K, and the content of humic acids .

2.2.4 NUTRIENT AND ENERGY FLUXES CHANGES The contributions of ants to nutrient cycling are expected to be more significant in poor than in fertile soils (Paysen 2007). In fertile environments with low organic matter and complex trophic webs, ants speed up the return of nutrients held in the bodies of animals to the soil (Folgarait 1998). Ants gather large amounts of food and the food residues are an essential source of nutrient increase (Paysen 2007). An increase in nutrient content is also due to quicker mineralization (Kendrick et al, 2015).

2.2.5 ANTS AND VEGETATION Plant species connected with ant nests usually differ from species growing in adjacent areas (Folgarait 1998) since they boost germination and seedling survival as well as plant growth and seed production (Lindsey and Skinner, 2001). Ant bioturbation can also affect nearby vegetation through the continuous heaping of the soil which may support the persistence of some yearly plants that would otherwise suffer from rivalry in dense meadow (Dostál et al 2005).

2.3 SPECIES DIVERSITY Mostly in ecological studies, species diversity is the collective single value to settle community structure (Hamilton 2005). First proposed in the 1960’s (Chesson 2000), species diversity has become a typical measure in methodologies of many ecological fields. The diversity indices help in finding quantitative estimates of biological variability to compare biological entities with

5 discrete components in space and time (Chesson 2000). Species diversity customarily involves two aspects which are species richness and species abundance (Chesson 2000).Species richness measures the total number of species in any given habitat (Hamilton 2005) while species abundance is the total quantitative estimate of species in a community (RíosCasanova and Bestelmeyer, 2008).

2.4 ANTS AND ENVIROMENTAL GRADIENTS 2.4.1 ALTITUDE A study on altitudinal distribution of leaf litter ants along a transect in primary forests on mount Kinabalu, Sabah Malaysia was done by Bruhl and Carsten in 1999. The rainforest systems stretched from dipterocarp hill forest to dwarf forest of the highest altitudes (560, 800, and 1150). The total ant fauna on the litter gradient found was 283 with 55 genera with the number of ant species declining exponentially without proof of a peak in species richness at midelevations. Basing on this study altitudinal ranges of species are very slim therefore elevation gradients have a high species richness and serve as a key example of biodiversity hotspot (Brühl and Carsten, 1999). Elevation gradients in phylogenetic structure of ant communities disclose interplay of biotic and abiotic restraints on diversity that is along each transect set in another investigation of the gradients, ant species density declined with elevation (Machac et al ,2011).

2.4.2VEGETATION/SOIL Deblauwe and Dekoninck (2007) studied the diversity and distribution of ground dwelling ants in a lowland rain forest in Cameroon where they concentrated on the effect of vegetation type on ant species diversity, activity and composition. The results of this study showed that vegetation type/soil significantly influenced the ground dwelling and arboreal ant assemblages. These differences were not only clarified by vegetation or soil type but mainly by the developmental stage of vegetation types (Deblauwe and Dekoninck, 2007).

2.4.3 LANDSCAPE AND SEASONALITY Landscape and seasonality environmental variables and their impact on ant diversity were studied by Marques and DelClaro( 2006) in a tropical savanna area were they found out that the chief diversity values were found in open areas, diurnal period and for vegetation substrate. They also revealed that there was no seasonal difference in the occurrence of genera and that the ant fauna species richness of the area was comparatively rich as compared to other savanna areas (Marques and DelClaro, 2006).

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2.4.4 TEMPERATURE The distribution of ants in a soy bean field on soil and plants was examined with environmental factors assessed with standard multiple regression analysis (Kidd and Apperson, 1984).. Ant activity on soil was sturdily influenced by soil and air temperature while activity on plants was predominantly related to air temperature. More ants were found foraging on the soil (cooler temperatures) than on soy bean plants and this did not change significantly over each 24h sample period (Kidd and Apperson, 1984).

2.4.5 LATITUDE AND RAINFALL An examination was made by Andersen et al (2015) using a standardized sampling protocol along a 600 km transect in Northern Australia where ant diversity was tested within a single biome (tropical savanna) to find out if it decreases with increasing latitude (as a surrogate of temperature) and declining rainfall as is expected for biodiversity in general. The result showed that patterns of ant diversity in Australian savannas do not conform to global patterns of biodiversity were diversity declines with increasing latitude and decreasing rainfall. It is believed to be due to the lack of significant temperature change across the latitudinal gradient (Andersen et al , 2015).

2.5 ANT DIVERSITY AND DISTURBANCE GRADIENTS 2.5.1 ROAD CONSTRUCTION The construction of roads is thought to influence the size and shape of surrounding remnant habitat which were investigated in order to show if they influence the diversity of ants or if they alter the microenvironment parameters. The distance from all road edges had a significant impact on species richness on highways giving the conclusion that road construction leads to a decrease in species diversity (Lassau and Hochuli, 2003).

2.5.2 FIRE A study conducted by Vasconcelos et al (2016) analyzed the effects of fire on the abundance and alpha diversity of ants based upon published over the past 70 years. The result of the study was t overally fire reduced ant diversity by 18 percent but had no effect on ant abundance. There was a significant variation in the effect of fire on ant diversity amongst vegetation types, that is fire significantly decreased ant diversity in forests especially in tropical forests whereas there was no change in deserts, grasslands and savanna. Similarly fire had a strong negative mean effect on ant diversity in sites where it is uncommon, but it did not significantly affect diversity where it is

7 a recurrent phenomenon (Vasconcelos et al , 2016). Furthermore a test was done by Vaunderwoude and Andersen ( 1997) to examine the biogeography and structure of ant communities and three sites were monitored two with a distinct long term burning history and the other unburned. Species richness and abundance at the burnt sites were similar but substantially higher than at the unburned site (Vaunderwoude and Andersen, 1997).

2.5.3 AGRICULTURE Many studies have been done in relation to ant diversity and agriculture, firstly ant diversity was examined by ElBokl et al (2015) at six sites under animal husbandry with three sites being control sites which were free from such a practice. Substantial differences in ant species diversity were apparent among the sites. The spatial variation among the study sites recorded the highest percent of species number and abundance at the control sites hence in brief this reflected that husbandry had an effect on ant species diversity due to variations in habitat characteristics at the study sites (ElBokl et al , 2015). Samples were also collected in 3 communities to associate species richness, abundance and species composition. The results showed that there was a greater ant species richness in a forest as compared to a garden while vacant lots were intermediate hence showing that growing of crops leads to a decline in species richness and abundance (Uno et al , 2010). Nowadays agriculture involves plantation establishment and on this a study was carried out by Pacheco et al (2009) on a pine plantation in Brazil to find out the litter ant diversity. The number of species was significantly higher in the control site (secondary plantation) than in the pine forest (Pacheco et al , 2009).

2.5.4 DEFORESTATION A study was done by Barlow et al (2007) to investigate the influence of disturbance, in particular fuel wood extraction. The results of the study showed that disturbance at a site leads to a decrease in ant diversity as it was lower in the disturbed site compared to the conserved one (Barlow et al , 2007). In Singapore the effect of forest disturbance (disturbed vs undisturbed) on ant diversity showed that there was no statistically significant difference in mean ant species richness and abundance even though the undisturbed forests had a higher species richness than the deforested one (Chong and Li, 2003).

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CHAPTER 3

METHODOLOGY

The study was carried out in areas around Bindura, a town located in Mashonaland C,entral province of Zimbabwe 88km northeast of Harare. The dominant soils in the area can be classified as red clays varying from silt clay loam to clay. The dominant biome is that of Miombo woodlands which is dominated by Brachystegia spiciformis and Julbernardia globiflora. The mean annual precipitation ranges from 650 to 1400 mm with more than 95% falling between November and March (summer season). The average temperature of Bindura is 19. 4 0C.

The first study (Fig 3.1) was at Matangira farm about 10km along the BinduraHarare road representing the agriculture land use in a field that was under maize crop ( Zea mays ). The second study site was an Acacia woodland in Simona about 8km along the BinduraHarare road representing the plantation land use. This area was dominated by Acacia polyacantha tree species. The third and final site was at Green Hill forest which is a natural Miombo woodland dominated by Brachystegia spiciformis, Brachystegia boehmii and Julbernardia globiflora.

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3.1 STUDY AREA

Fig 3.1: Map showing location of the study area.

3.2 DATA COLLECTION For the purpose of this study 4 parallel transect lines 10 meters apart of about 75 meters in length were constructed at each site running from south to the north. Five sampling points 15 meters apart were set on each transect and baits (bait 1 sugar, bait 2 jam, bait 3 peanut butter, bait 4 tuna and bait 5 honey in order to capture ground ants) randomly placed at these sampling points along transects. Five trees/stalks parallel to the transect lines being at least 15 meters apart were randomly chosen and the 5 bait determinants were applied to the chosen trees/stalks in the same order in order to capture arboreal ants (Fig 3.2). The 25 baits were monitored over a 5 hour period with the hand collection method being used to capture the ants. Each sampling point was visited at least 3 times with a maximum of 4 minutes being spent at each point for ant collection and bait replenishment. The collected ants were immediately put in vials containing 70 percent alcohol for preservation of the ants and then sent to the laboratory for identification. This

10 procedure was repeated at each site. All sampling was done between 9:00 am and 14:15 pm so as to standardize collection and reduce distinctions as a result of time and temperature differences. 3.3 ANTS IDENTIFICATION A dissecting microscope was used to identify key descriptive features of the ants and a field guide to insects of (by Picker) was used for ant species identification to genus and species level. Species were also assigned to one out of the nine functional groups based on the Neotropical ant classification (GarcíaMartínez et al , 2015) and categorizing ants into groups of ecologically similar species helps in the analysis of ant composition in the area (Bharti e t al , 2013).

3.4 DATA ANALYSIS The Shannon wiener index was used to calculate diversity. The Shannon Index of diversity (H′) which is an information statistic index which assumes that all species are represented in a sample was calculated using the formula: H’ = ∑ (pi) × ln (pi), where pi is the proportional abundance of a species and ln is the natural logarithm (Morris et al , 2014) .

For ant abundance that is the number of individuals observed for each different species encountered within the community (McGill et al . 2007) across habitat types the General Linear Model (GLM) univariate analysis was used to test for differences and the least significant difference (LSD) post hoc tests were used to further detect differences in abundance across sites at p < 0.05 significance level. Species richness that is the number of species encountered in a community (Brown et al , 2007) of the three sites was calculated and the results from the treatment groups were compared using the fisher’s exact test. This test of association was also used in the determination of comparisons on functional abundance as well as functional richness. Analysis of similarity, ANOSIM, (Davies et al , 2012) was used to test for significant differences in ant species composition between pure natural stands and the agricultural field. The Rstatistic is a measure of similarity of assemblages with values ranging between 1 and 1, and values closer to 1 indicate dissimilarity between assemblages. In order to visualize differences in ant species composition between Miombo, Acacia and Agricultural field, nonmetric multidimensional scaling (NMDS) iterated fifty times in order to achieve a global optimum was

11 applied. The ANOSIM and NMDS analyses were carried out using Primer software v 6.1.1(Davies et a l. 2012).

` A A A A

10m

B B B B

C C C C

D D D D

E E E E

FIG 3.2: Diagram showing sampling points

KEY

Sampling point A sugar bait, B jam bait, C peanut butter bait, D tuna bait, E honey bait Tree/ stalk sampling point

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CHAPTER 4 4.1RESULTS A total of 827 ant collections from 9 species were made across the 3 study sites (Table 4.1)

Table 4.1 Ant species collected at the study sites. The dash indicates that the species was absent at a particular site. SPECIES MIOMBO ACACIA FIELD Polyrhachis gagates 179 101 30 Myrmicaria natalensis 73 119 Melonopsis punctaticeps 49 3 custodiens 53 18 16 Linepithema humile 23 14 Tetraponera natalensis 13 Plectrotena mandibularis 42 peringueyi 62 10 Messor capensis 22

4.2 ANT DIVERSITY Based on the Shannon index of diversity, Miombo woodland had higher ant species diversity compared with the agricultural field and the acacia woodland (Table 4.2).

Table 4.2 Shannon diversity index across the study sites.

Diversity model Miombo Acacia Field H(Shannon) 1.74 1.31 1.30

4.3 ANT ABUNDANCE Site had a significant effect (F 2.85 =6.118, P<0.001) on ant abundance. Ant abundance varied significantly (P<0.001) between the Miombo woodland and Acacia woodland, Miombo woodland and Agricultural field and the Acacia woodland and Agricultural field. The fishers exact test showed that there was significant variation of functional abundance between sites

(P=0,199) (Fig 4.1a), however Bait showed no significant effect (F 2.85 = 0.958, p value = 0.434) on ant abundance (Fig 4.1b).

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a b

FIG 4.1 a: Proportional functional abundance across the three sites. FIG 4.1b: proportional bait abundance across the three sites.

4.4 ANT SPECIES RICHNESS Species richness was higher in the Miombo woodland (7) followed by the Acacia woodland (6) and then Agricultural field (4). There was no significant variation in the species richness of the Miombo woodland (p=0.265) as compared to the Acacia woodland (p=0.241) and the Agricultural field (p=0.265) as shown in Fig 4.2a. The fisher’s exact test showed no significant variation in the functional richness across the sites as shown in Fig 4.2b

a b

FIG 4.2a Bait richness across the three sites.4.2b functional richness across the three sites.

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4.5 SIMILARITY ANALYSES Analysis of similarity revealed differences in ant assemblages among the three habitats with a significant difference among habitats (Table 4.3). The nMDS showed that the Miombo woodland, Acacia woodland and agricultural field harbor different ant species (Fig 4.3).

Table 4.3

Rstatistic comparison over the study sites

Sites R statistic P-value Global R 0.431 0.001 Acacia vs. Miombo 0.388 0.016 Acacia vs . Field 0.428 0.016 Miombo vs. Field 0.452 0.008

FIG 4.3: Non metric multidimensional scaling (NMDS) ordination of the Miombo woodland, Acacia woodland and the Agricultural field.

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CHAPTER 5

DISCUSSION

A common effect of habitat modification on the ant fauna is a change in abundance and species richness across sites. Contrary to expectations based on global biodiversity patterns in relation to habitat modification and the diversity of ants, this study showed a low ant abundance and species richness in disturbed habitats and vice versa in the undisturbed.

5.1 SPECIES DIVERSITY Based on the Shannon index of diversity, Miombo woodland had higher ant species diversity compared with the agricultural field and the acacia woodland. This is mainly accredited to the conjoint associations with the vegetation in an area (Marques and DelClaro 2006). The relative low species diversity due the low number of ants in overall (abundance=827) as well as the low number of species richness (9) found in this study in relation to former ones can be related to the use of one methodology (baiting) given the fact that a combination of methodologies is an efficient way to sample ant fauna (Folgarait 1998).

5.2 ANT ABUNDANCE The lowest number of ants (70) was found in the agricultural Field compared to the 277 and 480 found in an Acacia plantation and the Miombo woodland respectively thereby supporting the significant effect of site on ant abundance as well as the variation in functional abundance across sites. This confirms the study by Lassau and Hochuli(2003) in which they attributed these differences between site abundance to greater resource heterogeneity (Lassau and Hochuli 2003) which is great in Miombo in terms of litter mainly. These resources are less accessible in monoculture in this case the maize field and the acacia polyacantha woodland (Pacheco et al 2009) (this one especially because of the allopathic effects caused by acacia trees).These differences can be attributed to the differences in vegetation structure (Deblauwe and Dekoninck 2007), altitude (Brühl et al . 1999; Machac et al. 2011), landscape (Marques and DelClaro 2006) and latitude (Andersen e t al 2015). The most abundant ant species across all sites was the Polyrhachis gagates and this is due them preadapting to the post disturbance conditions(El Bokl et al . 2015).

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5.3 SPECIES RICHNESS Species richness is a vital measure for several ecological education and conservation approaches (Ribas et al , 2012).Species richness was highest in the Miombo woodland (7) as to the Acacia (6) and the Field (4) just as expected in global biodiversity. A study Pacheco et al 2009 showed that secondary forest has a greater species richness than that of a plantation due to the higher tree species richness in this case Brachystegia spiciformis , Brachystegia boehmii and Julberbnadia globiflora compared to the one tree species in the Acacia woodland (acacia polyacantha) and one species maize in the Field. In general the plant composition of monoculture understory is poor(Lassau and Hochuli 2003). The second factor determining this is greater food availability, favorable abiotic and microclimatic conditions which may support higher ant species (Pacheco et al , 2009) . Results showed that Acacia and Field being under monoculture, had different species richness and this according to El boki et al 2015 can be due to agricultural practices such as irrigation (increase in soil moisture) and pesticides which have a negative effect upon ant species richness and biodiversity at large(El Bokl et al. 2015). Regardless of the Acacia being a disturbed habitat Messor capensis was not found at the site but in the field, this is accredited to it being a generalist and an opportunist (Uno et al , 2010).

5.4 NMDS DISPLAY PATTERNS In this test there was no significant distance between samples in a site since the plots were close to each other indicating relative similarity in terms of the species found in a site but as for the distance between sites, there was a significant distance between the sites hence this shows and supports the fact that site does actually have an effect on the diversity of ants.

5.5 LIMITATIONS TO THIS STUDY The sites of this study were chosen for their known activities, microhabitat variables such as ambient temperature, gradient, light intensities and soil structure were not measured and may contribute to the variation observed among the sites within the various determinants, However a standard data collection time was adhered to in order to try and minimize these effects.

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CHAPTER 6 CONCLUSION AND RECOMMENDATION

6.1 CONCLUSION

The study concluded that the diversity of ants was influenced by habitat type. The Miombo habitat promoted high diversity of ants with Acacia and the Field following respectively probably due to variations in habitat conditions. The study also showed a higher functional abundance and richness in the Miombo woodland compared to the Acacia woodland and the Agricultural field that the abundance are not always supporting the greatest functional richness therefore with all this the hypothesis of this study is accepted.

6.2 RECOMMENDATIONS 6.2.1FUTURE STUDIES Habitat destruction has led to the loss of many local flora and fauna hence more ecological studies should be conducted to determine the various impacts of such disturbance in different taxon groups especially arthropods which are still understudied locally. The future studies on ant diversity should include more gradients such as latitude, fire, canopy cover, and plant species diversity among many others. This will increase reliability of the results since limitations are reduced therefore results have less bias. Furthermore, future studies will need to be done over long periods which incorporate all seasons hence this will clearly identify the objective that will be at hand.

6.2.2 MANAGEMENT In order to reduce the loss of ant diversity in habitats under human influence, there is need to engage in rotation methods in both the plantations and in agricultural fields.

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REFERENCES

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APPENDICES APPENDIX 1

Tests of Between-Subjects Effects Dependent Variable: abundance Source Type III Sum of df Mean Square F Sig. Squares Corrected Model 2571.260 a 37 69.494 2.593 .001 Intercept 3358.348 1 3358.348 125.320 .000 Site 327.903 2 163.952 6.118 .004 Bait 103.724 4 25.931 .968 .434 species 571.164 10 57.116 2.131 .040 site * Bait 104.995 8 13.124 .490 .857 site * species 7.726 3 2.575 .096 .962 Bait * species 82.931 7 11.847 .442 .870 site * Bait * species 56.166 2 28.083 1.048 .359 Error 1259.517 47 26.798 Total 11877.000 85 Corrected Total 3830.776 84 a. R Squared = .671 (Adjusted R Squared = .412)

APPENDIX 2

Dependent Variable: abundance LSD (I) site (J) site Mean Difference Std. Error Sig. 95% Confidence Interval (I-J) Lower Bound Upper Bound field 5.55 * 1.518 .001 2.50 8.60 Acacia miombo -4.10 * 1.280 .002 -6.67 -1.53 Acacia -5.55 * 1.518 .001 -8.60 -2.50 Field miombo -9.65 * 1.468 .000 -12.60 -6.70 Acacia 4.10 * 1.280 .002 1.53 6.67 miombo field 9.65 * 1.468 .000 6.70 12.60 Based on observed means. The error term is Mean Square(Error) = 26.798. *. The mean difference is significant at the 0.05 level.

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APPENDIX 3

Homogeneous Subsets

Multiple Comparisons Dependent Variable: abundance LSD (I) Bait (J) Bait Mean Difference Std. Error Sig. 95% Confidence Interval (I-J) Lower Bound Upper Bound Jam 3.06 1.736 .084 -.43 6.56 Peanut Butter 2.28 1.658 .176 -1.06 5.61 Honey Sugar 2.28 1.768 .203 -1.27 5.84 Tuna 3.02 1.768 .095 -.54 6.57 Honey -3.06 1.736 .084 -6.56 .43 Peanut Butter -.79 1.757 .657 -4.32 2.75 Jam Sugar -.78 1.860 .677 -4.52 2.96 Tuna -.05 1.860 .980 -3.79 3.70 Honey -2.28 1.658 .176 -5.61 1.06 Jam .79 1.757 .657 -2.75 4.32 Peanut Butter Sugar .01 1.788 .997 -3.59 3.60 Tuna .74 1.788 .681 -2.86 4.34 Honey -2.28 1.768 .203 -5.84 1.27 Jam .78 1.860 .677 -2.96 4.52 Sugar Peanut Butter -.01 1.788 .997 -3.60 3.59 Tuna .73 1.890 .700 -3.07 4.54 Honey -3.02 1.768 .095 -6.57 .54 Jam .05 1.860 .980 -3.70 3.79 Tuna Peanut Butter -.74 1.788 .681 -4.34 2.86 Sugar -.73 1.890 .700 -4.54 3.07 Based on observed means. The error term is Mean Square(Error) = 26.798.

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