The development of novel bioremediation systems has widespread
benefits for human health and natural ecosystems. Optimization of such systems
is only possible with a thorough understanding of the processes that drive
bioremediation. This thesis developed novel understanding of carbon sources and
cycling relationships for microbial communities that are integral in controlling
contaminant fate in two contaminated environments. In the first case (Chapter 2),
biodegradation in the soil microbial community was determined to be the primary
pathway for recalcitrant petroleum pollutant removal. Microbial uptake and
metabolism of petroleum hydrocarbons was conclusively demonstrated via 14C
analysis of their PLFA biomarkers. This microbial community was the most 14C
depleted bacterial system detected in an environmental system to date. In
addition, complete mineralization of petroleum carbon was demonstrated with 14C
analysis of soil COz. The second paper (Chapter 3) identified unique Phospholipid
Fatty Acid (PLFA) biomarkers and stable carbon isotopic fractionation patterns
for heterotrophic and autotrophic bacterial communities of an acid mine drainage
(AMD) system. The characteristic isotopic fractionations observed during
biosynthesis of PLF A biomarkers in autotrophic versus heterotrophic metabolic
pathways provided the basis for a model capable of elucidating the relative roles
of these members of the microbial community in the environment. The major
implications of the knowledge developed in this thesis, are two new methods to identify microbial carbon cycling pathways and processes in contaminated environments. These advances may lead to new methods for mitigating the effects of contamination in environmental systems through better understanding of the microbial processes at the contaminated sites. / Thesis / Master of Science (MSc)
Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/21644 |
Date | 09 1900 |
Creators | Cowie, Benjamin |
Contributors | Slater, Gregory, Geography and Earth Sciences |
Source Sets | McMaster University |
Language | English |
Detected Language | English |
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