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Title: Embedding individual-based plankton ecosystem models in a finite element ocean model
Author: Lange, Michael
ISNI:       0000 0004 5355 7670
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2014
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Computational models of the ocean plankton ecosystem are traditionally based on simulating entire populations of microbes using sets of coupled differential equations. However, due to recent advances in high-performance computing, a new class of individual-based models (IBM) has come to the fore, which uses computational agents to model individual sub-populations of marine plankton. Although computationally more expensive, these agent-based models offer features that cannot be re-created using population-level dynamics, such as individual life cycles, intra-population variability and an increased stability over parameter ranges. The main focus of this thesis is the implementation and verification of an embedded modelling framework for creating agent-based plankton ecology models in Fluidity-ICOM, a state-of-the-art ocean model that solves the Navier-Stokes equations on adaptive unstructured finite element meshes. Since Fluidity-ICOM provides an interface for creating population-based ecology models, a generic agent-based framework not only enables the integration of existing plankton IBMs with adaptive remeshing technology, but also allows individual and population-based components to be used within a single hybrid ecosystem. This thesis gives a full account of the implementation of such a framework, focusing in particular on the movement and tracking of agents in an unstructured finite element mesh and the coupling mechanism used to facilitate agent-mesh and agent-agent interactions. The correctness of the framework is verified using an existing agent-based ecosystem model with four trophic levels, which is shown to settle on a stationary annual attractor given a stable cycle of annual forcing. A regular cycle of phytoplankton primary production and zooplankton reproduction is achieved using a purely agent-based implementation and a hybrid food chain version of the model, where the two top-level components of the ecosystem are modelled using Eulerian field equations. Finally, a standalone phytoplankton model is used to investigate the effects of vertical mesh adaptivity on the ecosystem in a three-dimensional mesh.
Supervisor: Field, Anthony ; Gorman, Gerard Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available