Thesis (doctoral)--Swedish University of Agricultural Sciences, 2006. / Thesis documentation sheet inserted. Appendix reprints three papers and manuscripts co-authored with others. Includes bibliographical references. Also partially issued electronically via World Wide Web in PDF format; online version lacks appendix.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 53-62). Also available on the World Wide Web.

The PLFA profiling method was adopted and used to determine changes in microbial community structure and abundance along natural and human-induced environmental gradients. The presented studies were based on field sampling campaigns combined with targeted laboratory experiments. According to the aims of particular studies, microbial PLFA fingerprinting was combined with the auxiliary below- and aboveground ecosystem characteristics to identify the drivers of microbial responses to environmental changes or with 13C-labelling and metagenomics to obtain more complex information about running processes and involved microorganisms.

Thesis (Ph. D.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 125-136). Also available on the World Wide Web.

Thesis (Ph. D.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 85-98). Also available on the World Wide Web.

Thesis (doctoral)--Swedish University of Agricultural Sciences, 2002. / Abstract inserted. Appendix reprints four papers and manuscripts co-authored with others. Includes bibliographical references. Also partially issued electronically via World Wide Web in PDF format; online version lacks appendix.

The environmental impact of anthropogenic disturbances such as agriculture, on the soil ecosystem, and particularly on soil microbial structural and functional diversity, is of great importance to soil health, conservation and remediation. Therefore, this study assessed the effects of various land use and management practices on both the structural (genetic) and functional (catabolic) diversity of the soil bacterial and fungal communities, at two long-term sites in KwaZulu-Natal. The first site is situated at Baynesfield Estate, and the second at Mount Edgecombe Sugarcane Research Institute. At site 1, the land uses investigated included soils under pre-harvest burnt sugarcane (Saccharum officinarum, Linn.) (SC); maize (Zea mays, Linn.) under conventional tillage (M); permanent kikuyu (Pennisetum clandestinum, Chiov) pasture (KIK); pine (Pinus patula, Schiede) plantation (PF); and wattle (Acacia mearnsii, De Wild) plantation (W), all fertilized; and undisturbed native grassland (NAT) that had never been cultivated or fertilized. At site 2, a sugarcane (Saccharum officinarum × S. spontaneum var. N27) pre-harvest burning and crop residue retention trial was investigated. The treatments studied included conventional pre-harvest burning of sugarcane with the tops removed (Bto), and green cane harvesting with retention of crop residues on the soil surface as a trash blanket (T). Each of these treatments was either fertilized (F) or unfertilized (Fo). The polymerase chain reaction (PCR), followed by denaturing gradient gel electrophoresis (DGGE) were used to determine the structural diversity, and community level physiological profiling (CLPP) using BIOLOG plates, the catabolic diversity. In addition, the soils were analysed with respect to selected physicochemical variables, and the effects of these on the soil microbial communities were determined. Replicate soil samples (0–5 cm) were randomly collected from three independent locations within each land use and management, at both sites. Soil suspensions for the CLPP analyses were prepared from fresh soil subsamples (within 24 h of collection) for the bacterial community analyses, and from 8-day-old soil subsamples (incubated at 4°C to allow for spore germination) for the fungal community analyses. BIOLOG EcoPlates™ were used for the bacterial CLPP study and SF-N2 MicroPlates™ for the fungal analysis, the protocols being adapted and optimized for local conditions. This data was log [X+1]-transformed and analysed by principal component analysis (PCA) and redundancy analysis (RDA). For PCRDGGE, total genomic DNA was isolated directly from each soil subsample, and purified using the MO BIO UltraClean™ soil DNA Isolation kit. Protocols were developed and optimized, and fragments of 16S rDNA from soil bacterial communities were PCR-amplified, using the universal bacterial primer pair 341fGC/534r. Different size 18S rDNA sequences were amplified from soil fungal communities, using the universal fungus-specific primer pairs NS1/FR1GC and FF390/FR1GC. Amplicons from both the bacterial and fungal communities were fingerprinted by DGGE, and bands in the fungal DGGE gels were excised and sequenced. The DGGE profiles were analysed by Bio-Rad Quantity One™ Image analysis software, with respect to band number, position, and relative intensity. Statistical analyses of this data then followed. Soil properties [organic C; pH (KCl); exchangeable acidity; total cations (ECEC); exchangeable K, Ca and Mg; and extractable P] were determined by PCA and were shown to have affected the structural and catabolic diversity of the resident microbial communities. At Baynesfield, canonical correspondence analysis (CCA) relating the selected soil variables to bacterial community structural diversity, indicated that ECEC, K, P and acidity were correlated with CCA1, accounting for 33.3% of the variance, whereas Mg and organic C were correlated with CCA2 and accounted for 22.9% of the variance. In the fungal structural diversity study, pH was correlated with CCA1, accounting for 43.8% of the variance, whereas P, ECEC and organic C were correlated with CCA2, and accounted for 30.4% of the variance. The RDA of the catabolic diversity data showed that the same soil variables affecting fungal structural diversity (organic C, P, ECEC and pH) had influenced both the bacterial and fungal catabolic diversity. In both the bacterial and fungal RDAs, organic C, P and ECEC were aligned with RDA1, and pH with RDA2. However in the bacterial analysis, RDA1 accounted for 46.0%, and RDA2 for 27.5% of the variance, whereas in the fungal RDA, RDA1 accounted for only 21.7%, and RDA2 for only 15.0% of the variance. The higher extractable P and exchangeable K concentrations under SC and M, were important in differentiating the structural diversity of these soil bacterial and fungal communities from those under the other land uses. High P concentrations under M were also associated with bacterial catabolic diversity and to a lesser extent with that of the soil fungal communities under M. Similarly, the higher organic C and exchangeable Mg concentrations under KIK and NAT, possibly contributed to the differentiation of these soil bacterial and fungal communities from those under the other land uses, whereas under PF, the high exchangeable acidity and low pH were possibly influencing factors. Under W, low concentrations of P and K were noted. Other factors, such as the presence/absence and frequency of tillage and irrigation, and the diversity of organic inputs due to the diversity of the above-ground plant community, (in NAT, for example) were considered potentially important influences on the nature and diversity of the various land use bacterial and fungal communities. At Mount Edgecombe, CCA showed that organic C and Mg had a significant effect on soil bacterial structural diversity. Organic C was closely correlated with CCA1, accounting for 58.7% of the variance, whereas Mg was associated with CCA2, and accounted for 41.3% of the variance. In the fungal structural diversity study, ECEC and pH were strongly correlated with CCA1 and accounted for 49.1% of the variance, while organic C was associated with CCA2, accounting for 29.6% of the variance. In the functional diversity studies, RDA showed that both bacterial and fungal community catabolic diversity was influenced by soil organic C, pH, and ECEC. In the bacterial analysis, RDA1 was associated with organic C and pH, and accounted for 43.1% of the variance, whereas ECEC was correlated with RDA2, accounting for 36.9% of the variance. In the fungal analysis, RDA1 was correlated with ECEC and accounted for 47.1% of the variance, while RDA2 was associated with pH and organic C, accounting for 35.8% of the variance. The retention of sugarcane harvest residues on the soil surface in the trashed treatments caused an accumulation of organic matter in the surface soil, which did not occur in the pre-harvest burnt sugarcane. This difference in organic C content was a factor in differentiating both bacterial and fungal communities between the trashed and the burnt treatments. Soil acidification under long-term N fertilizer applications caused an increase in exchangeable acidity and a loss of exchangeable Mg and Ca. Thus, as shown by CCA, a considerably lower exchangeable Mg concentration under F compared to Fo plots resulted, which was influential in differentiating the bacterial and fungal communities under these two treatments. In the structural diversity study at Baynesfield, differences were found in bacterial community species richness and diversity but not in evenness, whereas in the fungal analysis, differences in community species richness, evenness and diversity were shown. The soil bacterial and fungal communities associated with each land use were clearly differentiated. Trends for bacterial and fungal diversity followed the same order, namely: M < SC < KIK < NAT < PF < W. At Mount Edgecombe, no significant difference (p > 0.05) in bacterial structural diversity was found with oneway analysis of variance (ANOVA), but two-way ANOVA showed a slight significant difference in bacterial community species richness (p = 0.05), as an effect of fertilizer applications. A significant difference in fungal species richness (p = 0.02) as a result of management effects was detected, with the highest values recorded for the burnt/fertilized plots and the lowest for the burnt/unfertilized treatments. No significant difference was shown in species evenness, or diversity (p > 0.05), in either the bacterial or the fungal communities. In the catabolic diversity study at site 1, the non-parametric Kruskal-Wallis ANOVA showed that land use had not affected bacterial catabolic richness, evenness, or diversity. In contrast, while fungal catabolic richness had not been affected by land use, the soil fungal community catabolic evenness and diversity had. At site 2, the land treatments had a significant effect on soil bacterial community catabolic richness (p = 0.046), but not on evenness (p = 0.74) or diversity (p = 0.135). In the fungal study, land management had no significant effect on the catabolic richness (p = 0.706), evenness (p = 0.536) or diversity (p = 0.826). It was concluded, that the microbial communities under the different land use and trash management regimes had been successfully differentiated, using the optimized protocols for the PCR-DGGE of 16S rDNA (bacteria) and 18S rDNA (fungi). Sequencing bands produced in the 18S rDNA DGGE, enabled some of the soil fungal communities to be identified. CLPP of the soil microbial communities using BIOLOG plates showed that, on the basis of C substrate utilization, the soil bacterial and fungal communities’ catabolic profiles differed markedly. Thus, it was shown that the different land use and management practices had indeed influenced the structural and catabolic diversity of both the bacterial and fungal populations in the soil. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2011.

Thesis (Ph.D.)--University of Wyoming, 2008. / Title from PDF title page (viewed on August 7, 2009). Includes bibliographical references.

Thesis (Ph. D.)--Oregon State University, 2011. / Printout. Includes bibliographical references (leaves 123-135). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Canterbury, 2006. / Typescript (photocopy). Includes bibliographical references (leaves 237-268). Also available via the World Wide Web.