Thesis (MScFor) (Forest and Wood Science)--University of Stellenbosch, 2003. / Planting of upperstorey trees along boundaries has been introduced in KabaleUganda with good reception from local farmers. Trees have been planted along agricultural fields, but both Alnus acuminata and Grew/lea robusta out-compete food crops. Managing competition between trees and crops for water, light, and nutrients to the benefit of farmers is a determinant of successful agroforestry. The scarcity and fragmentation of farmland coupled with the hilly nature of Kabale, highlights the need to address the question of tree-crop competition for resources if the technology of on-farm tree planting is to be widely disseminated and adopted in its different guises. Five-year old trees of A acuminata and G. robusta were subjected to treatments of pollarding, or a combination of pollarding and one side root pruning and compared with unpruned controls. The objectives were to assess their potential in reducing competition with food crops and providing firewood to farmers as well as their effects on tree growth. Pollarding has many benefits to farmers because it provides firewood and stakes for climbing beans, it reduces competition for resources between trees and crops and enables continued tree planting on-farm. Continued on-farm tree planting alleviates problems associated with limited land and contributes to environmental resilience. To ensure this, effect of pollarding and root pruning of upperstorey boundary trees of A acuminata and G. robusta was tested on 12 farmers' fields in Kabale. Food crops (beans and maize) grown in the sequence beans-maize-beans, grew very well at less than 50 em from trees that had been pollarded and root pruned one side. In general, pooled data from 12 sites over 5 m away from trees indicated that a combination of pollarding and root pruning increased bean yield by 240% and maize by 154%, while pollarding alone increased bean yield by 181% and maize yield was increased by 123% in comparison to non-pruned trees. However, pollarding and root pruning treatments reduced tree growth rates.Notable was more competition with crops by A. acuminata than by G. robusta. This was attributed to differences in root architecture, diameter at breast height (dbh) sizes, crown spread and crown density between the two species. Five-year-old A. acuminata had bigger dbh (12.40 cm), wider crown spread (6 m) and a dense crown, while G. robusta had dbh 10.82 em, 3 m crown spread and a light crown. A. acuminata also had more branches per tree (34) compared to G. robusta with only 25. These factors influence water uptake, light penetration through the canopy and transpiration rates, and thus affect tree-food crop competition. It is concluded that pollarding and root pruning have a great potential to reduce tree-crop competition, thereby paving the way for continued on-farm tree planting. The effect of pollarding on timber quality, moisture seepage into timber through the cut surface, if any, and the extent of its damage are areas for further research. The rate of root recovery is also to be followed closely to determine an appropriate frequency for cutting back of roots to recommend to farmers how often they need to prune their trees. It is also suggested that a thorough study be conducted on the amount of water uptake from the soil by each of the species Alnus acuminata and Grevillea robusta. This will help further explain the differences in competition between the two species.

Thesis (MSc) -- Stellenbosch University, 1996. / ENGLISH ABSTRACT:Principle objectives of this study were to investigate the ecological feasibility of sustained utilization of mopane, using Venetia Limpopo Nature Reserve as a pilot study area. The study was limited to three different mopane dominated vegetation types on the reserve with most research being conducted in C.mopane woodland. Results can be summarized as follows: 1. Colophospermum mopane is ubiquitous on VLNR. 2. C.mopane woodland has the deusest mopane growth of the three vegetation types and highest densities are found on soils (OaB, VaB, Du, SwB & VaA) in association with C.mopane woodland. There seems to be a correlation between mopane density and soil type. 3. Largest mopane trees according to height and circumference were found in C.mopane/C.apiculatum open woodland. There is no significant difference between height and circumference on different soil types. 4. Most senility occurs in C.mopane shrubland and there is a significant difference in senility between mopane associated with different soils on which this vegetation type occurs. 5. Oldest average ages per tree were fo•.md in C.mopane woodland while growth rates were fastest in C.moparse!C.apiculatum open woodland. 6. There is a significant positive correlation between total and charcoal weights for mopane. Total and charcoul weights per tree were highest for C.mopane/C.apiculatum open woodland, while weights per hectare were highest for C.mopane woodland. Soils could not positively be associated with this trend. 7. Mopar.e lends itself to harvesting, especially C.mopane ••10odland in the Endora, Lizzulea and Hilda areas. Winter months seem to be most desirable for harvesting activities. Hand felling in elongated patches (increases ecotone boundary) is recommended where labour is cheap. A harvesting strategy of between 25% and 50% would make the operation economically viable and ecologically acceptable. An optimum harvesting rate of 27% is suggested by a harvesting model developed specifically for this mopane data. 8. Total herbivore densities, distribution and species proportions can be expected to change following bush clearing. Habitat for grazers should increase due to an increased grass production. Habitat for browsers should not be influenced much. Effect of noise and human disturbance during harvesting, especially for elephants is negligible, as hunting activities already take place on VLNR. 9. Grass production would increase but quality should decrease after harvesting, due to an increase in low quality opportunistic species, especially if soil disturbance takes place. Grass quality is best in association with herbaceous species such as Salvadora angustifolia. Carrying capacity for grazers should increase after harvesting as a result of habitat change and grass biomass increase. 10. Total browse production would decrease but leaf biomass should increase on remaining trees as they have improved water availability due to Q lack of intra­ specific competition. Higher seed production and more flowering takes place at lower tree densities. Greatest advantages for browsers after harvesting, is the fact that leaves become senescent later in autumn and that spring leaf flush takes place earlier thus prolonging bro\'se availability. / AFRIKAANSE OPSOMMING:Die hoof doelwitte van hierdie studie was om te bepaal wat die invloed van die oes van mop nie op die ekologie sou wees as dit op 'n volgehoue basis plaasvind en tot w•atter mate mopanie geskik is vir hou skoolvervaardiging. Die navorsing is op die Venetia Limpopo Natuureservaat in slegs drie van die belangrikste mopanie veldtipes uitgevoer met die oorgrote meerderheid van die navorsing in die C.mopane bosveld. Die resultate van die studie kan soos volg opgesom word: 1. Colophospermum mopane is alomteenwoordig op die VLNR. 2. Die C.mopane bosveld het die hoogste digtheid van al drie veldtipes en word ook geassosieer met sekere grondtipes (OaB, VaB, Du, SwB & VaA) wat eie is aan hierdie spesifieke veldtipe. Daar blyk 'n korrelasie te wees tussen die digthede van mopanie en grondtipes. 3. Die grootste mopanie borne, ten opsigte van hnogte en omtrek, word in die C.mopane/C.apiculatum oop bosveld aangetref. Daar is nie 'n beduidende verskil tussen die hoogte en omtrek van mopanie op die verskillende grondtipes nie. 4. Die C.mopane struikveld toon die meeste seniliteit ten opsigte van die persentasie kruin dood. Daar is 'n definitiewe aanduiding dat seniliteit ooreenstem met sekere grondtipes veral met betrekking tot die mopanie struikveld. 5. Die C.mopane bosveld het gemiddeld die oudste borne terwyl die C.mopane/C.apiculatum oop bosveld die vinnigste groeikoers toon. Die bogenoemde feite het 'n ver0and met die grondtipes. 6. Daar is 'n posltiewe korrelasie tussen die totale gewig en die houtskoolgewig van mopanle. Die S\vaarste borne is in die C.mopane!C.apiculatum oop bosveld aangetref, terwyl die swaarste gewig per hektaar in die C.mopane bosveld aangetref is. Gewig kon nie met grondt pes gekorreleer word nie. 7. Die mopanie in die C.mopane bosveld is geskik vir die oes vir houtskool, veral in die Endora, Lizzulea en Hilda gebiede. Dit is raadsaam om die borne in verlengde stroke per hand af te kap (vergroot die ekotoongebied), veral waar arbeid goedkoop is. 'n Oesstrategie van tussen 25% en 50% vir mopanie word aanbeveel om dit ekonomies en ekologies aanvaarbaar te maak. 'n Optimum oesstrategie van 27% word aanbeveel deur 'n oes model wat spesifiak vir hierdie mopane data opgestel is. 8. Daar kan verwag word dat na die oes van mopanie die getalle asook verspreidingspatrone van alle hoefdierspesies kan verander. 'n Voordeel van lae mopanie digthede is dat die verspreiding van die blaarbiomassa ewerediger oor die seisoene sal geskied. Grasvreters word bevoordeel vanwee die verandering in habitat. Die effek van geraas en ander oesbedrywighede op olifante behoort klein te wees aangesien jagaktiwiteite alreeds op diereservaat toegepas word en hulle redelik gewoond daaraan behoort te wees. 9. Grasproduksie behoort toe te neem terwyl die kwaliteit daarvan afneem as gevolg van opportunistieslae kwaliteit grasspcsies wat toeneem na die oes van mopanie, veral as die grand tydens oesaktiwiteite versteur word. Die beste kwaliteit gras word in assosiasie met kruidagtige spesies, veral Salvadora angustifolia, gevi.nd. As gevolg van die verandering in habitat asook die toename in grasbiomassa neem die drakrag vir grasvreters na die oes an mopanietoe. 10. Di.e totale blaarbi.)massa behoort na die oes van mopanie af te neem, maar behoort terselfdertyd op die oorblywende borne as gevolg van die afname in kompetisie vi= watr en anrler natuurlike hulpbronne toe te neem. Hoer persentasies blomvorming en saadproduksie vind by laer boomdigthede plaas. Die grootste enkele voordeel vir blaarvreters, na die oes van mopanie, is die feit dat die blare later in die herfs afval en vroeer in die lente uitbot en dus die voedselbeskikbaarheid vir blaarvreters verleng.

The importance of ecological systems in supporting social systems has been identified as one of the most important facets of sustainable development. Consequently, a number of international and local laws and policy interventions have been established to ensure that natural resource use remains sustainable. In rural areas, overdependence on fuel wood has commonly been identified as one of the biggest threat to forestry ecosystems. This in turn has led to environmental degradation that includes among others species depletion, soil erosion and decline in water and air quality. Based on the myriad problems caused by over-reliance on fuel wood, this study sought to identify usage, management and perceived implication of woodland exploitation in Port St Johns local municipality in the Eastern Cape, South Africa. Using interviews and questionnaires for key respondents in the local community, the study identified two key threats to socio-ecological stability resulting from wood fuel exploitation namely; high poverty levels and lack of coordination in the management of wood fuel resources. Apart from using fuel wood for domestic use, local fuel wood exploitation has been commercialized to augment household incomes. Lack of coordination in the management of natural resources has also created a vacuum in the exploitation and management of fuel wood resources. The study did not have inclination towards statistics such as chi-square and t-tests since the research questions and objectives did not refer to any relationship or significance level. The study recommends non-wood based alternative sources of energy, improved coordination and harmonization of functions among different stakeholders and emphasis on collaboration between traditional and local governance in the management fuel wood and the local physical environment. The study further recommends resuscitation of indigenous knowledge and socio-ecological stability

The objectives of this study were to determine the loading of dead and down forest fuels in 6 forest cover types on the upper Coastal Plain of Virginia, specifically in the Richmond National Battlefield Park, and to determine the relationships between the fuels and the vegetation. The forest fuels and vegetation were sampled in stands of the following cover types: pine, oak-pine, mixed hardwood-pine, oak, mixed hardwood, and oak-mixed hardwood. The planar intersect method was utilized to quantify the woody fuels. and the forest floor was sampled in fixed area plots. The weight. volume, depth. and species of fuel particles was determined for each stand sampled in the Park, and this information was combined for an estimate of fuel loading by cover type. The overstory trees were sampled within prism plots, and the understory was sampled in fixed area plots. Standard forestry information was collected for each sampled stand, and estimates of species dominance, density, frequency and importance were determined. In general, the fuel loading was not different between the six cover types as determined with ANOVA procedures. due to the large variation of loads within each. The loading of certain sizes of fuel particles were different between a few cover types, due to both the influence of the overstory species and the site they had occupied. For example, the 1-hr. time-lag branch fuel loading was significantly greater in the oak cover type than in the pine or mixed hardwood cover types. Another significant difference was in the forest floor loads: the mixed hardwood cover type had a lighter forest floor than the pine or oak-pine cover types. This was most likely due to the higher quality of sites upon which the mixed hardwood stand were found, and the higher palatability of litter produced by these species, which would favor the decomposition of litter more than conditions found in the pine or oak-pine cover types. To quantify relationships between the fuel loads and forest vegetation and site characteristics, Spearman's rank correlation coefficients were calculated between all the variables. Many significant relationships were found, though all but one correlation coefficient was under 0.51: total forest floor load and forest floor depth had a correlation coefficient of 0.75. Forest and site variables significantly related to fuel loadings were tested for their predictive value with multiple regression statistics. The resulting set of regressions had low coefficients of determination and varying levels of precision; their usefulness would depend on the level of sampling intensity and precision one would want to expend to get an estimate of fuel loading in a stand. If a rough estimate requiring little time in the field is desirable, then these regressions would be useful. / Master of Science

Text in English with summaries and keywords in English, Venda and Sepedi / Fuelwood remains a crucial source of energy among the vast majority of rural households because of its availability and affordability in comparison with most energy alternatives. Approximately 17 million people in South Africa live in communal lands where fuelwood can be harvested easily and freely by households, with 80% of the overall fuel consumed for domestic purposes extracted from burning fuelwood. The rapid-excess trends of fuelwood consumption – aggravated by population growth, agricultural and household settlement expansions – pose utmost challenges for community development. Overharvesting of fuelwood can result in fuelwood scarcity, loss of biodiversity, excessive land clearance and soil erosion. This study evaluated the factors that influence fuelwood consumption in households at the Thulamela Local Municipality. The study utilised mixed research methods, comprising quantitative and qualitative methods. A semi-structured questionnaire consisting of both closed and open-ended questions was used to collect data from the households. The collected data was mainly qualitative data (nominal and categorical data) and the researcher used the frequency menu to summarise the data and cross tabulation menu in the Statistical Package for Social Scientists (SPSS) version 25. For cross tabulation, the researcher used the Chi-square (χ2) test to measure the degree of association between two categorical variables. If the p-value is less than 0.05, there is a significant association between variables – thus, the variables dependent on each other. The study found that socio-economic characteristics such as monthly income, employment status, gender, educational level of the household head, number of employed household members, energy expenditure and type of occupation play a significant role in the factors that influence fuelwood consumption. As a result of these factors, fuelwood energy is still being used as a primary energy source by most households to meet their domestic needs for cooking and water heating – despite most of them being electrified. Additionally, lack of environmental education, the erratic electricity supply and staggering living conditions which drive widespread poverty in rural areas contribute to the extensive fuelwood consumption among households. The study highlighted the recommendations on mitigation measures that can be used to reduce extensive fuelwood consumption. These recommendations include encouraging the use of renewable energy and modern energy technologies such as biogas and solar energy, together with improved cooking stoves to help reduce overexploitation of natural resources and prevent indoor air pollution which is associated with heart disease and immortality. There is also a need to raise environmental awareness. It is through education that people’s perceptions, attitudes and behaviour regarding fuelwood consumption practices can be changed. The promotion of sustainable development through harvest control and afforestation can significantly reduce deforestation, loss of biodiversity, fuelwood scarcity and soil erosion. / Khuni dzi kha ḓi shumiswa sa tshiko tshihulwane tsha mafulufulu kha miṱa minzhi ya mahayani ngauri dzi a wanala na u swikelelea musi dzi tshi vhambedzwa na dziṅwe nḓila dza mafulufulu. Vhathu vha swikaho miḽioni dza 17 Afrika Tshipembe vha dzula mahayani hune vha kona u reḓa khuni hu si na vhuleme nahone nga mahala, ngeno zwivhaswa zwi swikaho 80% zwi shumiswaho miḓini zwi tshi bva kha khuni. Maitele maṅwe a tshihaḓu a kushumiselwe kwa khuni – a tshi ṋaṋiswa na nga nyaluwo ya vhathu, u engedzea ha vhulimi na vhupo ha vhudzulo – zwi ḓisa khaedu kha mveledziso ya tshitshavha. U reḓa khuni lwo kalulaho zwi nga vhanga ṱhahelelo ya khuni, u xelelwa nga mutshatshame wa zwi tshilaho, u ṱangula mavu na mukumbululo wa mavu. Ngudo iyi yo ḓiimisela u ela zwivhumbi zwi ṱuṱuwedzaho u shumiswa ha khuni miḓini ngei kha Masipala Wapo wa Thulamela. Ngudo yo shumisa ngona dza ṱhoḓisiso dzo ṱanganaho dzi re na ngona khwanthethivi na khwaḽithethivi. Mbudzisambekanywa dzo dzudzanywaho dzi re na mbudziso dza phindulo nthihi na dza phindulo ndapfu dzo shumiswa u kuvhanganya data miḓini. Data yo kuvhanganyiwaho kanzhi ndi yo sedzaho ndeme (ya tshivhalo na khethekanyo) ngeno muṱoḓisisi o shumisa menyu wa tshivhalo tsha zwithu u nweledza data na menyu wa thebulu dzi leluwaho kha Statistical Package for Social Scientists (SPSS) vesheni ya vhu 25. U itela thebulu dzi leluwaho, muṱoḓisisi o shumisa ndingo dza Chi-square (χ2) u ela tshikalo tsha nyelelano vhukati ha zwithu zwivhili zwo fhambanaho. Arali ndeme ya p i ṱhukhu kha 0.05, hu na u elana hu hulwane vhukati ha zwithu zwi vhambedzwaho – zwithu izwi zwi dovha zwa ṱalutshedzana. Ṱhoḓisiso yo wana uri zwiṱaluli zwa ikonomi na matshilisano sa mbuelo ya ṅwedzi, tshiimo mushumoni, mbeu, ḽeveḽe ya pfunzo ya ṱhoho ya muḓi, tshivhalo tsha vhathu vha shumaho muṱani, mbadelo dza fulufulu na mushumo une muthu a u shuma zwi na mushumo muhulwane kha zwithu zwi ṱuṱuwedzaho u shumiswa ha khuni. Nga ṅwambo wa zwithu izwi, khuni dzi kha ḓi shumiswa sa tshiko tshihulwane tsha fulufulu kha miḓi minzhi u swikelela ṱhoḓea dzavho dza hayani dza u bika na u wana u dudedza – naho vhunzhi havho vhe kha muḓagasi. Nṱhani ha izwo, u sa vha na pfunzo ya vhupo, nḓisedzo ya muḓagasi ine ya dzula i tshi shanduka na maga a kutshilele a konḓaho ane a vhanga vhushai ho andaho kha vhupo ha mahayani zwi vhanga u shumiseswa ha khuni miḓini. Ngudo dzo sumbedzisa themendelo kha maga a u lulamisa ane a nga shumiswa u fhungudza u shumiseswa ha khuni. Themendelo idzi dzi katela u ṱuṱuwedza tshumiso ya mafulufulu ḽo vusuludzwaho na thekhinoḽodzhi dza fulufulu dza musalauno sa bayogese na fulufulu ḽa masana a ḓuvha, kathihi na zwiṱofu zwa u bika zwo khwiniswaho u thusa u fhungudza u tambiseswa ha zwiko zwa mupo na u thivhela tshikafhadzo ya muya nga ngomu zwine zwa vhanga vhulwadze ha mbilu na dzimpfu. Hu na ṱhoḓea ya u ita mafulo a zwa vhupo. Ndi nga kha pfunzo hune kuvhonele kwa vhathu, kusedzele kwa zwithu na vhuḓifari havho maelana na kushumiselwe kwa khuni zwa nga shandukiswa. U bveledzwa ha mveledziso i sa nyeṱhi nga kha ndango ya khaṋo na u ṱavhiwa ha miri zwi nga fhungudza vhukuma u fhela ha maḓaka, u lozwiwa ha mutshatshame wa zwi tshilaho, u konḓa ha khuni na mukumbululo wa mavu. / Dikgong tša go bešwa di tšwela pele go ba methopo o bohlokwa wa enetši gareng ga bontši bja malapa a dinagamagaeng ka lebaka la ge di hwetšagala le go se ture ga tšona ge di bapetšwa le mekgwa ye mengwe ya enetši. Tekano ye e ka bago batho ba dimilione tše 17 ka Afrika Borwa ba dula mafelong a magaeng fao dikgong di ka kgonago go rengwa gabonolo le ka tokologo ke malapa a, fao e lego gore 80% ya palomoka ya dibešwa tšeo di šomišwago ka gae di hwetšwago go dikgong. Lebelo leo ka lona dikgong di hwetšago ka lona gore di tle di bešwe – leo le mpefatšwago ke go gola ga setšhaba, temo le go oketšega ga madulo a batho – le tliša ditlhohlo tše kgolo tlhabollong ya setšhaba. Go rema dikgong go fetišiša go ka feletša ka go hlaelela ga tšona, tahlegelo ya phedišano ya diphedi tša mehutahuta, go rema mehlare ka fao go fetišišago le kgogolego ya mobu. Dinyakišišo tše di ikemišeditše go sekaseka mabaka ao a huetšago go šomišwa ga dikgong ka malapeng ka Masepaleng wa Selegae wa Thulamela. Dinyakišišo tše di šomišitše mekgwa ya dinyakišišo ye e hlakantšwego, ye e lego wa dinyakišišo tša bontši le wa dinyakišišo tša boleng. Dipotšišonyakišišo tšeo di beakantšwego ka seripa tše di nago le bobedi dipotšišo tša di nago le dikgetho le dipotšišo tšeo di nyakago gore motho a fe maikutlo a gagwe di šomišitšwe go kgoboketša tshedimošo ka malapeng. Tshedimošo ye e kgobokeditšwego e bile kudu tshedimošo ya boleng (ya dipalo le ya go hlophiwa) gomme monyakišiši o šomišitše menyu wa bokgafetšakgafetša go dira kakaretšo ya tshedimošo le go menyu wa go bea dilo ka dintlha ka Sehlopheng sa Dipalopalo sa Bašomi ba tša Mahlale a Leago (SPSS) bešene ya 25. Go bea dilo ka dintlha, monyakišiši o šomišitše teko ya Chi-square (χ2) go ela bogolo bja kamano magareng ga diphapano tše pedi tša magoro. Ge p-value e le ye nnyane go 0.05, go na le kamano ye bohlokwa magareng ga diphapano – ke gore, diphapano di a hlalošana. Dinyakišišo di hweditše gore dipharologantši tša ekonomi ya setšhaba tša go swana le letseno la kgwedi ka kgwedi, maemo a mošomo, bong, maemo a thuto a hlogo ya lapa, palao ya maloko a ka lapeng ao a šomago, tšhomišo ya tšhelete go enetši le mohuta wa mošomo di raloka tema ye bohlokwa ka mabakeng ao a huetšago go šomišwa ga dikgong. Ka lebaka la mabaka a, enetši ya dikgong e sa šomišwa bjalo ka methopo o bohlokwa wa enetši ke malapa a mantši ka nepo ya go fihlelela dinyakwa tša bona tša ka gae tša go apea le go ruthufatša dintlo – go sa kgathale gore bontši bja tšona ke tša mohlagase. Godimo ga fao, tlhokego ya thuto ya mabapi le tikologo, kabo ya mohlagase ye e sa tshepišego le maemo a bophelo ao a hlobaetšago ao a hlohleletšago bohloki ka dinagamagaeng di tsenya letsogo go tšhomišo ya dikgong go fetišiša ka malapeng. Dinyakišišo di hlagiša ditšhišinyo tša mabapi le go fokotša tšhomišo ya dikgong go fetišiša. Ditšhišinyo tše di akaretšwa go hlohleletša tšhomišo ya mohlagase wa go dirišwa leswa le ditheknolotši tša enetši tša sebjalebjale tša go swana le gase ya tlhago le mohlagse wa sola, gotee le ditofo tša go apea tšeo di kaonafaditšwego ka nepo ya go fokotša go šomiša kudu methopo ya tlhago le go thibela tšhilafatšo ya moya ya ka dintlong e lego seo se amantšhwago le bolwetši bja pelo le mahu. Gape go na le tlhokego ya go tliša temošo ya tša tikologo. Ke ka go diriša thuto fao e lego gore maikutlo a batho, ditebelelo le maitshwaro a bona mabapi le ditiro tša tšhomišo ya dikgong a tlago fetošwa. Tšwetšopele ya tlhabollo ya go ya go iule ka taolo ya go rema dikgong le go bjala mehlare fao go ka fokotšago go rengwa ga mehlare, tahlegelo ya mehutahuta ya diphedi, tlhaelelo ya dikgong le kgogolego ya mobu. / Environmental Sciences / M. Sc. (Environment Management)

The survey has been carried out in North West Province within Rustenburg Local Municipality. This is an Urban Forestry research in which six sites including peri-urban, urban, suburban and semi-rural areas were selected for the study. The aim of the study was to determine the relationship between households and their local trees and forests. Forest in this context included community gardens, vegetation cover, open spaces, soil, water, productive sites and animals that form part of forest. Data collection was mainly based on questionnaires and covered sample of 272 households. Statistical Package of Social Sciences (SPSS) 15.0 using 5% sampling intensity (confidence level) was used in which the data has been represented by numbers. Analysis was based on determining households’ relationship with their trees and local forest, and how they influence forest productivity or development. With SPSS two techniques, regression model and descriptive statistics were applied to analyze quantitative and qualitative data. Regression model was significant in prediction of the dependent variable (Y) using independent variables (X), and proved to be a good model to analyze data for fuelwood, timber and forest food production. Descriptive statistics was important in counting number of times each category or variable is used. Participants had varying perceptions regarding the use of forest due to factors such as availability of forest resource, type of residence, and their living standard. Generally, households in suburban and urban areas value the forests for economic and environmental benefit, while the peri-urban and semi-rural households utilized their trees and forest to meet their energy demand. A large number of households consume forest food as compared to timber and fuelwood due to the availability of the resources. The Municipality as a whole is undergoing rapid development expected to continue throughout years. These developments are stimulated by mining activities and influx of people in the area. All these factors threaten the existing natural resources especially forest areas and water. Areas of these resources are declining due to the current demand for housing, new mining sites and continuous establishment of informal settlements. Trees and forest within peri-urban and semi-rural areas are in poor conditions as compared to urban and suburban areas. Poor waste management and poverty are issues aggravating the situation especially in poor developing sites that have been studied. Most agricultural sites have been transformed into residential areas, and thus exacerbating problems of food insecurity in the whole country. Household size has major influence in fuelwood, timber and forest food production as an increase or decrease in the size will determine the amount of consumption, production or development. Value for forest, access to forest, level of interaction and restrictions regarding the use of forest are also significant aspects contributing to forest productivity and development as they show the relationship that exists between forest and households. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2007.

This is a study of the creation and evolution of state forestry within colonial Kenya in social, economic, and political terms. Spanning Kenya’s entire colonial period, it offers a chronological account of how forestry came to Kenya and grew to the extent of controlling almost two million hectares of land in the country, approximately 20 per cent of the most fertile and most populated upland (above 1,500 metres) region of central Kenya . The position of forestry within a colonial state apparatus that paradoxically sought to both ‘protect’ Africans from modernisation while exploiting them to establish Kenya as a ‘white man’s country’ is underexplored in the country’s historiography. This thesis therefore clarifies this role through an examination of the relationship between the Forest Department and its African workers, Kenya’s white settlers, and the colonial government. In essence, how each of these was engaged in a pursuit for their own idealised ‘good forest’. Kenya was the site of a strong conservationist argument for the establishment of forestry that typecast the country’s indigenous population as rapidly destroying the forests. This argument was bolstered against critics of the financial extravagance of forestry by the need to maintain and develop the forests of Kenya for the express purpose of supporting the Uganda railway. It was this argument that led the colony’s Forest Department along a path through the contradictions of colonial rule. The European settlers of Kenya are shown as being more than just a mere thorn in the side of the Forest Department, as their political power represented a very real threat to the department’s hegemony over the forests. Moreover, Kenya’s Forest Department deeply mistrusted private enterprise and constantly sought to control and limit the unsustainable exploitation of the forests. The department was seriously underfunded and understaffed until the second colonial occupation of the 1950s, a situation that resulted in a general ad hoc approach to forest policy. The department espoused the rhetoric of sustainable exploitation, but had no way of knowing whether the felling it authorised was actually sustainable, which was reflected in the underdevelopment of the sawmilling industry in Kenya. The agroforestry system, shamba, (previously unexplored in Kenya’s colonial historiography) is shown as being at the heart of forestry in Kenya and extremely significant as perhaps the most successful deployment of agroforestry by the British in colonial Africa. Shamba provided numerous opportunities to farm and receive education to landless Kikuyu in the colony, but also displayed very strong paternalistic aspects of control, with consequential African protest, as the Forest Department sought to create for itself a loyal and permanent forest workforce. Shamba was the keystone of forestry development in the 1950s, and its expansion cemented the position of forestry in Kenya as a top-down, state-centric agent of economic and social development.

Text in English with abstracts in English, Sepedi and Venda / Access to firewood and other affordable energy sources is essential to the livelihoods of rural households in developing countries. Studies have been conducted to understand the reasons behind an extensive reliance on firewood in rural areas, especially in developing countries, despite improved electrification rates and a number of government policies introduced to encourage rural households to switch from traditional to modern fuels. This study aimed at assessing and thus understand the factors influencing the use of firewood by households in Ga - Malahlela village in Limpopo Province. Limited research has been conducted on firewood use, subsequent to improved electrification in rural areas in South Africa, hence it was to shed light on this little-explored subject on which the study was carried out. The assessment was based on household demographics and household energy use patterns, with a structured questionnaire being utilised to arrive at a detailed understanding of the factors that drive firewood use. It was established that firewood was still used to a significant degree, to satisfy household energy needs such as cooking, water heating and space heating. This was mainly due to the socioeconomic status of households. Socio-economic factors such as income, education level, household size and preference were found to be the factors exerting the greatest influence on the use of firewood among households in the study area. Psychological variables and the geographical location of the study area were also shown to promote the use of firewood. The study further revealed that, as indicated in the reviewed literature, households in the study area fuel stack and do not ascend the energy ladder. The reviewed literature further indicated that not all factors have equivalent significance in determining the behaviour and pattern of household energy use. This indicates that energy sources such as firewood are not completely discarded but are instead used in conjunction with modern energy sources such as electricity. In conclusion, this study established that despite the availability of electricity, as a result of poverty and the lack of free basic services such as free basic electricity, reliance on firewood in rural areas will continue. / Go hwetša dikgong le methopo ye mengwe ya dibešwa tšeo di rekegago go bohlokwa go mekgwa ya malapa a dinagamagaeng go hwetša dilo tše bohlokwa tša bophelo dinageng tšeo di hlabologago. Dithutelo di phethagaditšwe go kwešiša mabaka ao a thekgago kholofelo go dikgong mafelong a dinagamagaeng a dinaga tšeo di hlabologago le ge go na le ditekanyo tše di kaonafaditšwego tša tlhagišo ya mohlagase le palo ya melaotshepetšo ya mmušo yeo e tsebišitšwego go tutuetša malapa a dinagamagaeng go fetoga go tloga go dibešwa tša sekgale go iša go tša sebjale. Thutelo ye e ikemišeditše go lekola ka gona go kwešiša mabaka ao a huetšago malapa a Motsaneng wa Ga-Malahlela ka Profenseng ya Limpopo go diriša ya dikgong. Dinyakišišo tše lekantšwego di phethagaditšwe ka ga tirišo ya dikgong ka morago ga tlhagišo ya mohlagase yeo e kaonafaditšwego mafelong a dinagamagaeng ka Afrika Borwa, gomme e be e swanetše go fa tshedimošo ka ga hlogotaba yeo e hlohlomišitšwego gannyane gore thutelo ye e phethagatšwe. Tekolo ye e theilwe go dipalopalo ka ga malapa setšhabeng le mekgwa ya malapa ya go dirišwa dibešwa, ka go diriša lenaneopotšišo leo le beakantšwego gore go fihlelelwe kwešišo ye e hlalošago ka botlalo mabaka ao a hlohleletšago tirišo ya dikgong. Go lemogilwe gore dikgong di sa dirišwa ka bontši bjo bo bonagalago go kgotsofatša dinyakwa tša malapa tša enetši tše bjalo ka go apea, go ruthetša meetse le go ruthetša lefelo. Se se be se swanela gagolo ka lebaka la boemo bja ka moo ekonomi e amago tšwelopele ya malapa. Mabaka a ka moo ekonomi e amago tšwelopele ya setšhaba a go swana le ditseno, boemo bja thuto, bogolo bja lelapa le tšeo di ratwago go hweditšwe go ba mabaka ao a hlohleletšago khuetšo ye kgolokgolo go tirišo ya dikgong gare ga malapa thutelong ye. Dielemente tšeo di ka fetolwago le lefelo tikologong ye e itšeng tša thutelo le tšona di bontšhitšwe go godiša tirišo ya dikgong. Thutelo ye gape e utollotše gore, bjalo k age go šupilwe dingwalong tšeo di lekotšwego, malapa a lefelong la thutelo a latela mekgwa ya dibešwa tša mehutahuta gomme ga a latele manamelo a enetši. Dingwalo tšeo di lekotšwego di laeditše go ya pele gore ga se mabaka ka moka ao a nago le bohlokwa bjo bo lekanago go šupeng boitshwaro le mokgwa tša tirišo ya enetši ka malapeng. Se se šupa gore methopo ya enetši ye bjalo ka dikgong ga se ya tlogelwa ka gohlegohle eupša e dirišwa mmogo le methopo ya sebjale ya enetši ye bjalo ka mohlagase. Go ruma, thutelo ye e utollotše gore le ge go na le mohlagase, ka lebaka la bohloki le tlhaelo ya ditirelo tša motheo tša mahala tše bjalo ka mohlagase wa motheo wa mahala, kholofelo go dikgong dinagamagaeng e tlo tšwela pele. / U swikelela khuni na zwiṅwe zwiko zwa fulufulu zwine zwa swikelelea ndi zwa ndeme kha u tsireledza zwo teaho zwa vhutshilo kha miṱa ya vhupo ha mahayani kha mashango o no khou bvelelaho. Ngudo dzo farwa u itela u pfesesa zwiitisi zwa u ḓitika zwihulwane nga khuni kha vhupo ha mahayani kha mashango ane a khou ḓi bvelela zwi si na ndavha na u khwiniswa ha u dzheniswa ha muḓagasi na tshivhalo tsha mbekanyamaitele dza muvhuso dzo ḓivhadzwaho u ṱuṱuwedza miṱa ya vhupo ha mahayani u bva kha u shumisa zwivhaswa zwa kale u ya kha zwa ano maḓuvha. Ngudo iyi yo livhiswa kha u asesa na u pfesesa zwiṱaluli zwine zwa ṱuṱuwedza u shumiswa ha khuni nga miṱa ya Muvhunduni wa Ga-Malahlela Vunduni ḽa Limpopo. Ṱhoḓisiso dzi si nngana dzo itwa nga ha u shumiswa ha khuni hu tshi tevhela u dzheniswa ha muḓagasi vhuponi ha mahayani Afurika Tshipembe, ho vha u bvisela khagala nga ha zwiṱuku zwo wanululwaho kha thero heyi ye ngudo ya i bveledzisa. U linga ho vha ho ḓisendeka nga ngudamirafho ya miṱa na kushumisele kwa fulufulu miṱani, hu na mbudzisombekanywa dzo dzudzanywaho dzo shumiswaho u swikelela kha u pfesesa nga vhuḓalo zwiṱaluli zwine zwa ta u shumiswa ha khuni. Ho dzhielwa nṱha uri khuni dzi kha ḓi shumiswa nga maanḓa u ḓisa ṱhoḓea dza fulufulu miṱani u fana na u bika, u vhilisa maḓi na u dudedza vhudzulo. Hezwi zwo tea nga maanḓa kha vhuimo ha matshilisano a zwa ikonomi miṱani: zwiṱaluli zwa ikonomi ya matshilisano zwi ngaho sa mbuelo, vhuimo ha pfunzo, vhuhulu ha muṱa na zwo no takalelwa ho wanwa uri ndi zwiṱaluli zwine zwa shumisa ṱhuṱhuwedzo khulwane ya u shumiswa ha khuni vhukati ha miṱa ya vhupo ha ngudo. Variabuḽu dza saikhoḽodzhikhaḽa na vhupo ha ḓivhashango zwa vhupo ha ngudo zwo sumbedziswa u ṱuṱuwedza u shumiswa ha khuni. Ngudo yo isa phanḓa na u wanulusa uri, sa zwo sumbedziswaho kha maṅwalwa o sedzuluswaho, miṱa kha vhupo ha ngudo i kuvhanganya fulufulu ngeno hu sina u gonya ha tshanduko ya kushumisele kwa fulufulu. Maṅwalwa o sedzuluswaho o sumbedzisa a tshi i sa phanḓa uri a si zwiṱaluli zwoṱhe zwine zwa vha na ndeme i linganaho kha u ta vhuḓifari na kushumisele kwa fulufulu miṱani. Hezwi zwi sumbedza uri zwiko zwa fulufulu zwi ngaho sa khuni a zwo ngo laṱelwa kule tshoṱhe fhedzi zwi shumiswa zwo ṱanganyiswa na zwiko zwa fulufulu zwa ano maḓuvha zwi ngaho sa muḓagasi. Ri tshi pendela, ngudo iyi i ta uri na musi muḓagasi u hone, nga nṱhani ha vhushayi na ṱhahelelo ya tshumelo dza muḓagasi wa mahala wa mutheo u fana na muḓagasi wa mahala wa mutheo, u ḓitika nga khuni vhuponi ha mahayani hu ḓo ḓi bvela phanḓa. / Department of Environmental Science / M.A. (Environmental Science)