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Title: Modelling multivariate spatio-temporal structure in ecological data and responses to climate change
Author: Harris, V.
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2013
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In this study the behaviour of multivariate plankton communities and their relationships with climate is explored. Existing statistical methodology is adapted to analyse both the plankton communities and sea surface temperature. In the first part of this study a large scale exploratory analysis is applied using principal component analysis. Dominant temporal trends and spatial patterns for a number of indicator species and the joint responses of functional groups of species are found.The community analysis focuses on on the zooplankton and the phytoplankton, the latter respresented by diatoms. This research is novel because the full multivariate structure of the plankton data has not been studied across communities before. The common trends are regressed against different climate signals to determine dominant drivers and cluster analysis identifies regions based on species. In the second part ‘regime shifts’ described by changes in ecoregions are explored. Whilst changes in spatial patterns over time have been studied over indicator species, this study describes the shift across communities, providing an overview of how the ‘regime shift’ is differently expressed for the two species groups. To explore changes in biogeographical patterns, the data is then divided in to a pre-1985 and post-1985 regimes. The results show a northwards movement of zooplankton species and increased spatial structure across the diatom group, following the bathymetry. In the final part the model is used to predict vulnerability of different indicator species and the community as a whole to changes in climate drivers across space, which is used to find climate change ‘hotspots’. Vulnerability is defined as a significant change in abundance in response to a relatively small change in the climate signal. Vulnerability is also explored at different scales. These results highlight the spatial inhomogeneity of species responses and are of great interest to environmental policy makers.
Supervisor: Olhede, S. C. ; Murrell, D. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available