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Title: Carbon dynamics in terrestrial ecosystems
Author: Glanville, Helen C.
Awarding Body: Bangor University
Current Institution: Bangor University
Date of Award: 2012
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The objective of this thesis was to better understand the mechanistic control of carbon (C) cycling in two terrestrial ecosystems (agricultural grasslands and Arctic tundra), with an aim to identify the contribution of microbial respiration to below-ground C cycling. Firstly, I evaluated different techniques for measuring CO2 evolution from soil. I found that different in-situ chamber-based CO2 gas analyzers gave comparable results across contrasting ecosystems. However, the addition of collars to the CO2 chamber induces variable flux estimates due to the disturbance created upon collar insertion, severing root and mycorrhizal networks. In subsequent studies, I showed that microbial breakdown of individual dissolved organic C (DOC) components demonstrated good reproducibility when performed under either in-situ and ex-situ conditions. After validating the experimental techniques, they were then used to study C turnover in two plant-soil systems. In Arctic tundra, soil temperature was identified as the key driver initiating microbial and vegetation response to snow melt, thereby driving early season CO2 efflux. However, as the growing season progressed, soil water content was hypothesized to become a more important regulator of C turnover with older C compounds becoming more susceptible to decomposition as soil water content increases. In a grassland soil I found that soil microbial community composition does not correlate with increased rates of mineralization across a wide pH gradient. This suggests that abiotic drivers of respiration may directly influence microbial metabolic processes independent of community structure. Further research involving advanced molecular techniques (metabolomics, proteomics, transcriptomics) will help disseminate how metabolic processes are being influenced by different respiration drivers. The application of mathematical models to respiration data provides a more quantitative and mechanistic understanding of processes involved in soil C cycling. I found the fitting of exponential models to respiration data is a reliable proxy for describing substrate mineralization; however, the correct choice of model is critically dependent on the number of measurement points and length of experiment. The modelling approach was subsequently used to quantify the turnover of functional microbial C pools. By combining modelling with experimental measures of soil solution C concentration, we estimated that the microbial contribution to total soil respiration is ea. 18%. This research provides a more detailed understanding of how C constituents are processed by the microbial decomposer community to drive soil respiration. This is crucial to accurately model global terrestrial C fluxes in different ecosystems and to predict how these fluxes are likely to respond to future changes from both natural (e.g. climate change) and anthropogenic (e.g. land-use change) sources.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available