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Modelling Biodiversity Trends from Occurrence Records

Outhwaite, Charlotte Louise; (2019) Modelling Biodiversity Trends from Occurrence Records. Doctoral thesis (Ph.D), UCL (University College London). Green open access

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Abstract

Large-scale studies of biodiversity change are limited in their taxonomic coverage: a lot is known about the trends of groups such as birds, butterflies and mammals, but little is known about invertebrates and plants. This is due to the lack of abundance data for these groups. However, alternative data such as occurrence records are available for a vast range of species and advances in methodologies are enabling their robust analysis. Here, I analyse UK occurrence records using Bayesian occupancy modelling techniques to determine the status, patterns and drivers of change in less well-studied taxa. First, variations of an occupancy modelling framework were tested to determine whether methods could be improved. This resulted in a “random walk” model that could analyse sparse occurrence records while producing results with increased precision and reduced bias when compared to other variants. This enabled the application of the model to data for over 12,000 species from 32 taxa including vascular plants and numerous invertebrate groups. The resulting estimates of annual occupancy present new information on large-scale change from fine-grained data. Exploration of these estimates showed that trends are not consistent with those of well-studied taxa. Occupancy estimates were then used to assess change in three forms of biodiversity trend: local alpha diversity, regional alpha diversity and regional beta diversity. This revealed the multifaceted nature of biodiversity change and the need to monitor across metrics and scales. Finally, a Bayesian, multispecies, dynamic occupancy model was used to determine the effect of water quality on the population dynamics of freshwater invertebrates. This work highlights the potential of occurrence records to investigate biodiversity change and brings to light new information on many species that have not previously been studied at a national scale.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Modelling Biodiversity Trends from Occurrence Records
Event: UCL (University College London)
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Copyright © The Author 2018. Original content in this thesis is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment
URI: https://discovery.ucl.ac.uk/id/eprint/10064504
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