Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.581493
Title: The modelling of mixotrophy in the oligotrophic Atlantic
Author: Herrington, Sian Joscelyn
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2012
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Abstract:
In the oligotrophic Atlantic Ocean small algae are the dominant fixers of inorganic carbon. In situ experiments have shown that a large proportion of these algae are mixotrophs - eating bacteria (bacterivory) as well as obtaining energy from sunlight. Bacterivory performed by algae has implications for our understanding of the role of ultraplankton (<5 μm) in biogeochemical cycling. The motivation of this thesis is to explore how mixotrophy may be modelled in the subtropical Atlantic using a data driven approach. An ecosystem model incorporating ultraplankton mixotrophy was developed, constructed and parameterised using in situ data, initially through network analysis and later using a μ-Genetic Algorithm technique. The model highlights the key role of mixotrophy in the cycling of nutrients, in a region where fast nutrient turnover is important for the functioning of the ecosystem. In addition, the model reveals that bacterivory is the predominant route of nutrient acquisition for these mixotrophs and suggests that mixotrophy in this low nutrient region is an adaptive rather than a survival mechanism. This thesis also addresses wider questions related to model structure and assumptions. The need for an explicit dissolved organic phosphate variable in an ecosystem model for the oligotrophic Atlantic is questioned through in situ radio-nucleotide bioassay techniques. Additionally, ultraplankton spatial variability is statistically assessed and used to demonstrate that a zero-dimensional model is not necessarily applicable to an entire region, despite the ultraplankton community within that region being statistically similar according to multivariate analyses. Furthermore a comparison of in situ to remotely sensed data shows that ocean colour is limited in its ability to detect ultraphytoplankton, making the use of such data to calibrate and assess future models difficult. This thesis therefore not only contributes to our ability to model the oligotrophic Atlantic but more broadly to our understanding of the role of mixotrophs within it.
Supervisor: Martin, Adrian Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.581493  DOI: Not available
Keywords: GC Oceanography
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