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Modelling multivariate spatio-temporal structure in ecological data and responses to climate change

Harris, V; (2013) Modelling multivariate spatio-temporal structure in ecological data and responses to climate change. Doctoral thesis , UCL (University College London). Green open access

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Abstract

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.

Type: Thesis (Doctoral)
Title: Modelling multivariate spatio-temporal structure in ecological data and responses to climate change
Open access status: An open access version is available from UCL Discovery
Language: English
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/1388074
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