Modelling of physical and physiological processes controlling primary production and population dynamics of cyanobacteria

Michael Kehoe (2010). Modelling of physical and physiological processes controlling primary production and population dynamics of cyanobacteria PhD Thesis, School of Chemical Engineering, The University of Queensland.

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads
s41252316_PhD_abstract.pdf Abstract application/pdf 8.14KB 2
s41252316_PhD_totalthesis.pdf Final Thesis Lodgement. application/pdf 1.46MB 14
Author Michael Kehoe
Thesis Title Modelling of physical and physiological processes controlling primary production and population dynamics of cyanobacteria
School, Centre or Institute School of Chemical Engineering
Institution The University of Queensland
Publication date 2010-11
Thesis type PhD Thesis
Supervisor Dr. Kate O'Brien
Assoc. Prof. Michele Burford
Total pages 126
Total colour pages 2
Total black and white pages 124
Subjects 09 Engineering
Abstract/Summary Abstract The objective of this project was to apply a range of modelling techniques to increase understanding of how irradiance affects the growth and success of toxic cyanobacteria. The modelling methodology is a multiple-model approach, using data mining, empirical, mechanistic, and Eulerian models, applied to two species of toxic cyanobacteria; Cylindrospermopsis raciborskii, a toxic freshwater species which is spreading worldwide, and Lyngbya majuscula, an estuarine species responsible for water quality problems in Moreton Bay, Queensland, Australia. The aim of this thesis is to demonstrate how the use of multiple modelling methods increases our overall understanding of processes controlling cyanobacteria populations by applying models that range from a machine learning algorithm to a theoretical partial differential equation model. In particular, a range of different models, often in conjunction with experiments, are used to further define, adding to previous research, the ecological niche of C. raciborskii, and to provide insight into the physical processes controlling benthic light and nutrients affecting L. majuscula blooms. An Eulerian model was developed to determine the effects of thermocline behaviour on light competition between a model, neutrally buoyant, filamentous cyanobacteria specie and a model, buoyant, floating colonial, cyanobacteria specie. This model provides insight into the mechanisms that promote the growth of the toxic freshwater cyanobacterium Cylindrospermopsis raciborskii, which is observed to dominate in strongly stratified systems. The model tests the hypothesis that thermocline disturbance can influence which model species succeeds under light competition. The model results suggest that neutrally buoyant species are favoured by high turbulent mixing to a constant, preferably shallow, depth. Morphological constraints mean, all else equal, that there is a trade-off between floating velocity and resource-gathering efficiency that are favoured by different turbulent mixing conditions. The key result of this study is the definition of the turbulent mixing niche of filamentous cyanobacteria in general. Machine learner models were used in conjunction with field experiments to quantify the impact of wind speed and direction on benthic irradiance and nutrients available for the growth to the toxic cyanobacterium Lyngbya majuscula in Moreton Bay, Queensland, Australia. Random forest models were constructed to predict benthic irradiance for two sites in Moreton Bay. The importance of wind speed and direction in the benthic irradiance model suggest resuspension of sediment is important in controlling benthic irradiance at both sites. In particular this helps explain the initiation of Lyngbya majuscula blooms at one of the sites: Deception Bay. The initiation period of a large bloom in Deception Bay coincided with a 5-fold increase in benthic irradiance (100 µmol quanta m-2 s-1 up to 640 µmol quanta m-2 s-1) due to a change in wind fetch when the prevailing wind direction switched from the Southeast to the Northeast. This irradiance level matched the irradiance flux (700 µmol quanta m-2 s-1) found to be optimal in a published ecophysiological study of Lyngbya majuscula primary production. At one site, experiments and observations were conducted to quantify the influence of wind speed and direction on nutrient availability to L. majuscula. With a dominant controlling process identified, a simplified process model of resuspension can now be developed to predict benthic irradiance and water column nutrients. The method demonstrated the advantages of data interrogation to determine dominant processes to aid the development of parsimonious mechanistic models. The role of temperature in controlling primary production of C. raciborskii was assessed using field experiments. The primary production and irradiance (P-I) data was modelled using three techniques: empirical, mechanistic and machine learners. C. raciborskii primary production was found to increase with water temperature up to 28 oC (0.589 +/- 0.019 g C g chl a-1h-1) after which it dropped significantly to be lowest at 32 oC (0.108 +/- 0.001 g C g chl a-1h-1). The optimal temperature of 28 oC for C. raciborskii primary production is comparable to the optimal growth temperature for C. raciborskii recorded in literature. The results demonstrated how application of multiple models to P-I data can be used to define uncertainty in P-I parameters. The mechanistic model produced results consistent with commonly used empirical models but also produced behaviour consistent with the physiological processes on which it is based. The floating velocities of C. raciborskii trichomes (cylindrical conglomerates of cells) were quantified using a particle-tracking video microscopy method. Furthermore, the densities (977–989 kg m-3) of individual trichomes were quantified using the modified Stokes law. This is the first time this inverse method density calculation has been used. The Stokes equation was also used to make predictions of the influence of changes in water temperature on the floating velocities of a range of C. raciborskii trichome sizes. As temperature increases, the rising velocities of C. raciborskii trichomes are predicted to increase by a negligible amount because the relatively small trichome size means that the floating velocity of C. raciborskii is almost negligible (< 0.057 m/day). This thesis demonstrates that there is no preferable modelling methodology for understanding processes that control cyanobacteria populations. By choosing data appropriate modelling objectives and methodologies I was able to explore processes relevant to two cyanobacteria species more broadly than could have been possible from any one modelling methodology. Particularly, a combination of experimental data modelling and theoretical competition modelling allowed integration of the ecological niche and ecophysiology of the toxic cyanobacteria Cylindrospermopsis raciborskii. A key finding on Cylindrospermopsis raciborskii is that the turbulent niche that favours it in competition for light is consistent with the aquatic environments in which it is observed to dominate (Chapter 2).
Keyword Cylindrospermopsis raciborskii
modelling and simulation
primary production
machine learning
multiple models
Additional Notes 86,109

Citation counts: Google Scholar Search Google Scholar
Created: Tue, 30 Nov 2010, 18:50:15 EST by Mr Michael Kehoe on behalf of Library - Information Access Service