The Modelling of Mixotrophy in the Oligotrophic Atlantic
The Modelling of Mixotrophy in the Oligotrophic Atlantic
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 ?m) 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
?-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.
Herrington, Sian Joscelyn
f75d87de-449e-4373-930b-afda8e0f185a
1 December 2012
Herrington, Sian Joscelyn
f75d87de-449e-4373-930b-afda8e0f185a
Martin, Adrian P.
9d0d480d-9b3c-44c2-aafe-bb980ed98a6d
Herrington, Sian Joscelyn
(2012)
The Modelling of Mixotrophy in the Oligotrophic Atlantic.
University of Southampton, Ocean and Earth Science, Doctoral Thesis, 175pp.
Record type:
Thesis
(Doctoral)
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 ?m) 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
?-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.
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Herrington, Sian_2013PhD.pdf
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Published date: 1 December 2012
Organisations:
University of Southampton, Ocean and Earth Science
Identifiers
Local EPrints ID: 359061
URI: http://eprints.soton.ac.uk/id/eprint/359061
PURE UUID: 2c10835f-eace-430a-aceb-df1185756b31
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Date deposited: 23 Oct 2013 12:51
Last modified: 14 Mar 2024 15:15
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Contributors
Author:
Sian Joscelyn Herrington
Thesis advisor:
Adrian P. Martin
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