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Title: Application of synchronisation theory to plankton patchiness
Author: Guirey, Emma Jane
ISNI:       0000 0001 3522 0730
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2007
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This study applies a metapopulation dynamics approach to modelling a distribution of plankton by representing a region of ocean as an ensemble of plankton populations interacting through the stirring and mixing eects of the ow. The methods of synchronisation theory are applied within this framework to gain insight into emergent spatial structure in biophysical simulations. The manifestation of synchronisation, including statistically stable local clustering of populations, frequency-locking or phase-locking of the entire ensemble and fully synchronised dynamics, is found to depend upon: the biological model used; the strength of mixing between populations; the number of populations or, equivalently, spatial resolution of the modelled region; the level of mismatch between and spatial arrangement of population natural frequencies; the strength of stirring of the ensemble at spatial scales larger than the grid-cell. The study therefore highlights a number of biophysical modelling parameters determining the properties of emergent spatial structure in simulations of surface ocean biological dynamics. This study shows that persistent spatial heterogeneity (patchiness) can result from what intuitively should be a homogenising in uence: mixing can increase the level of disorder between the plankton populations. Furthermore, the work shows that synchronisation eects occur generically under a range of simulation scenarios, giving condence that synchronisation theory can explain some of the spatial structure, or `patchiness', observed in plankton distributions, and providing one possible answer as to how populations of planktonic organisms maintain coherent spatial structures under the mixing and stirring action of the oceanic flow.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QH301 Biology ; GC Oceanography