Abstracts in English, Afrikaans and Venda / The purpose of this study was to assess the diversity of epiphytic lichens growing on Acacia karroo, A. caffra and Jacaranda mimosifolia trees in Pretoria, and to investigate the influence of air pollution, land use, altitude and climate on lichen diversity. Lichen diversity was first studied at 12 sampling sites under different land use types (high traffic areas, residential areas and industrial areas) and in protected areas (open-air museums and nature reserves). The “European guidelines for monitoring lichen diversity as an indicator of environmental stress” were then tested in 29 sites using the same tree species and under two main land use types (“Industrial areas and busy roads” and “Parks and nature reserves”). Lichen Diversity Values (LDVs) were calculated for 164 trees. Correlations of LDVs and single lichen species with environmental parameters were studied by descriptive statistics, univariate analysis, Principal Component Analysis (PCA) and Generalized Linear Models (GLM). A naturality/alteration interpretative scale based on the percentile deviation of LDVs from natural conditions was developed for the first time in South Africa. Altogether 25 taxa, predominantly foliose and subtropical to tropical species, were recorded and are reported with their ecology and distribution. An identification key was developed for easy identification of species in the field. The highest lichen diversity was found in protected areas. The LDVs of Jacaranda are lower than values for both Acacia species. “Parks and nature reserves” have significantly higher LDVs than “industrial areas and busy roads”, as demonstrated by the PCA. The GLM models were significant for LDV and some lichen species. Sampling sites in industrial areas and the proximity of busy roads are negatively related to LDV and with the frequency of many lichen species. Higher atmospheric concentrations of NOx were negatively related to LDV and to the frequency of the species Candelaria concolor, Lepraria spp. and Pyxine cocoes. Culbersonia nubila and Lepraria spp. were respectively positively and negatively correlated with atmospheric SO2. The intensity of land use appears to have a negative impact on lichen diversity. In conclusion, lichens respond well to human disturbances in Pretoria and can be used as bioindicators of naturality/alteration. The European standardised monitoring method can be applied to estimate the degree of environmental alteration in South Africa, by adopting a stratified random sampling and a more flexible strategy for tree selection. / Die doel van hierdie studie is om die diversiteit van die epifitiese ligene op Acacia Karoo, A. caffra en Jacaranda mimosifolia bome in Pretoria te bepaal, en die uitwerking van lugbesoedeling, grondgebruik, hoogte en klimaat op die ligeendiversiteit te ondersoek. Die ligeendiversiteit is by 12 monsterneemterreine bestudeer. Sommige terreine het op grond met uiteenlopende gebruike (drukverkeergebiede, woongebiede en nywerheidsgebiede) en ander in beskermende gebiede (opelugmuseums en natuurreservate) voorgekom. Die “Europese riglyne vir die monitering van ligeendiversiteit as aanduiding van omgewingstres” is telkens by dieselfde boomspesies op 29 terreine gevolg. Die hoofsoorte grondgebruik van hierdie terreine was “nywerheidsgebiede en besige paaie” en “parke en natuurreservate”. Die ligeendiversiteitswaardes (LDW’s) van 164 bome is bereken. Die korrelasies tussen LDW’s, enkelligeenspesies en omgewingsparameters is aan die hand van beskrywende statistiek, eenveranderlikeontleding, ʼn hoofkomponentanalise (HKA) en veralgemeende lineêre modelle (VLM’s) bestudeer. ʼn Verklarende naturaliteit-/wysigingskaal wat op die persentielafwyking van LDW’s in natuurlike omstandighede berus, is vir die eerste keer in Suid-Afrika ontwikkel. Altesame 25 taksa, oorwegend digblarige en subtropiese tot tropiese boomspesies, tesame met die ekologie en verspreiding van elk, is geboekstaaf. ʼn Kensleutel waarmee spesies maklik in die veld uitgeken kan word, is ontwikkel. Die grootste ligeendiversiteit het in beskermde gebiede voorgekom. Die LDW’s van Jacaranda was laer as dié van die twee Acacia-spesies. Volgens die HKA het “parke en natuurreservate” beduidend hoër LDW’s as “nywerheidsgebiede en besige paaie” gehad. Die VLM’s vir LDW en sommige ligeenspesies was veelseggend. In nywerheidsgebiede en naby besige paaie was die LDW en die voorkoms van verskeie ligeenspesies laag. ʼn Hoë konsentrasie van NOx het ʼn negatiewe verband getoon met die LDW en die voorkoms van die spesies Candelaria concolor, Lepraria spp. en Pyxine cocoes. Daarteenoor het Culbersonia nubila en Lepraria spp. onderskeidelik positief en negatief met atmosferiese SO2 gekorreleer. Die intensiteit van grondgebruik benadeel blykbaar ligeendiversiteit. Ten slotte reageer ligene goed op menslike versteurings in Pretoria. Hulle kan as bioaanwysers van naturaliteit/wysiging gebruik word. Die gestandaardiseerde Europese moniteringsmetode kan toegepas word om die mate van omgewingswysiging in Suid-Afrika te skat deur gestratifiseerde, ewekansige steekproewe te neem en ʼn buigsame strategie in boomkeuring te volg. / Ndivho ya ngudo idzi ho vha u ela ha phambano ya nzulatshinya dza epiphytic lichens dzi aluwaho kha Muunga wa Sogani, Caffra na Muṱonḓowa wa Piṱori, u sedzulusa ṱhuṱhuwedzo ya tshikafhadzo, u shumiswa ha mavu, vhunṱha na kilima kha u fhambana ha nzulatshinya. Phambano ya nzulatshinya yo thoma u gudiwa kha saithi dza 12 dza sambula nga fhasi ha tshaka dzo fhambanaho dza tshumiso ya mavu (vhupo ha vhuendi, vhupo ha vhudzulo na vhupo ha dzifeme) na kha vhupo ho tsireledzwaho (miziamu yo vuleaho na kha tsireledzo ya mupo). Nyendedzi dza Yuropa dza u lavhelesa phambano ya nzulatshinya sa tsumbo ya “mutsiko kha mupo” dzo lingiwa kha saithi dza 29 hu tshi khou shumiswa miri ya tshaka dzi fanaho nga fhasi ha tshaka mbili dza ndeme dza tshumiso ya mavu (“vhupo ha dzifemeni na bada dzi re na vhuendi ho tsitsikanaho” na “phakha na fhethu ha tsireledzo ya mupo”). Ndeme dza Phambano ya Nzulatshinya (LDV) dzo rekanywa u itela miri ya 164. U elana ha LDV na tshaka dza nzulatshinya na phimo dza mupo zwo gudiwa nga mbalombalo dza ṱhalutshedzo, musaukanyo nga phambano nga nthihi, Musaukanyo wa Zwipiḓa zwa Ndeme (PCA) na Tshiedziswa Tswititi tsho Angaredzwaho (GLM). Tshikalo tsha ṱhalutshedzo ya tshanduko ya mupo zwo ḓisendeka nga u fhambana ha phesenthe ya LDV u ya kha nyimele ya mupo tsho bveledzwa lwa u thoma kha ḽa Afrika Tshipembe. Zwo ṱangana zwoṱhe, tshaka dza 25, dzine nnzhi dza vha nzulatshinya dza tshaka dza fhasi ha ṱiropika na kha ṱiropika dzo rekhodiwa na u vhigiwa na saintsi ya mupo yadzo ya phaḓaladzo. U topola ha ndeme ho bveledzwa u itela u kona u ḓivha dzitshaka nnḓa. Phambano khulwane ya nzulatshinya yo wanala kha vhupo ho tsireledzeaho. LDV dza muṱonḓowa dzi fhasi kha ndeme u fhira u itela tshaka dza Muunga. “Phakha na fhethu ha tsireledzo ya mupo” hu na LDV dza nṱha u fhira “vhupo ha dzifemeni na bada dzi re na vhuendi vhunzhi”, sa zwe zwa sumbedziswa nga kha PCA. Zwiedziswa zwa GLM zwo vha zwi zwa ndeme u itela LDV na tshaka dza nzulatshinya. Saithi dza tsumbonanguludzwa kha vhupo ha dzifemeni na u vha tsini ha bada dzi re na vhuendi ho tsitsikanaho dzi elana lu sa takadzi na LDV na tshivhalo tsha tshaka nnzhi dza nzulatshinya. Pfutelelo ya nṱha ya dzingamufhe ya NOx yo vha i sa elani zwavhuḓi na LDV na tshivhalo tsha dzitshaka dza Candelaria concolor, Lepraria spp. na Pyxine cocoes. Culbersonia nubila na Lepraria spp. dzo vha dzi tshi livhanywa zwavhuḓi na lu si lwavhuḓi na SO2 ya dzingamufhe. Kushumiselwe kwa mavu ku nga ku na masiandaitwa a si avhuḓi kha mutevhe wa nzulatshinya. Ndi tshi fhedzisa, nzulatshinya dzi fhindula zwavhuḓi u thithiswa nga vhathu Piṱori nahone dzi nga zwisumbedza vhutshilo ha tshanduko/mupo. Ngona ya tshilinganyo ya vhulavhelesi ya Yuropa i nga shumisa u anganyela tshikalo tsha tshanduko dza vhupo kha ḽa Afrika Tshipembe. Nga u dzhia tsumbonanguludzwa dzo dzudzanywaho nga zwigwada zwa tshayandivhiswa na tshiṱirathedzhi tshi shandukiseaho tsha munanguludzo wa miri. / Environmental Sciences / D. Phil. (Environmental 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)