Clarke, James Alan (2024) Estimating UK butterfly lifespans and abundances using citizen-science count data. Doctor of Philosophy (PhD) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.105060) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:105060)
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Official URL: https://doi.org/10.22024/UniKent/01.02.105060 |
Abstract
With increasing amounts of environmental change, whether that be due to a changing climate, habitat destruction or habitat fragmentation, there is an increasing need to analyse available data in a way that allows us to best understand changes in abundance. A group of organisms for which we possess a wealth of data in the UK are butterflies. It has been shown that 52% of UK butterfly species have declined in abundance and 74% have declined in occurrence from 1976-2019. In this thesis we use citizen-science count data from the UK Butterfly Monitoring Scheme to produce robust estimates of ecologically interesting information, such as abundance, lifespan and phenology.
We begin by showing that it is possible to produce estimates of absolute abundance using citizen-science count data, rather than relative abundance. This is done by accounting for detectability by regressing on suitable environmental covariates, which are collected by volunteers performing the survey. These absolute abundance estimates are then used to determine differences in abundance trends for a selection of species when comparing to those generated using relative abundances.
We then demonstrate the possibility of using a stopover model to estimate adult lifespans using citizen-science count data and compare these to published results from capture-recapture studies. After this we fit the model in a multiyear format to share parameters across years and determine trends in lifespans over time. Once this is done we determine if accounting for lifespan in the model will impact the abundance trends produced.
Finally we estimate abundance trends at finer spatial scales across the UK. This is done by accounting for changing phenology, both spatially and temporally, using a multiyear model framework.
The updated forms of these models, as developed in this thesis, will provide more robust and accurate abundance estimates and trends. Furthermore, using a small selection of species we have shown that this can impact the extent and direction of the abundance trends that we produce.
Item Type: | Thesis (Doctor of Philosophy (PhD)) |
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Thesis advisor: | McCrea, Rachel |
Thesis advisor: | Dennis, Emily |
Thesis advisor: | Morgan, Byron |
DOI/Identification number: | 10.22024/UniKent/01.02.105060 |
Uncontrolled keywords: | abundance butterfly lifespan trends statistics citizen-science counts |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Funders: | NERC Environmental Omics Facility (https://ror.org/036g3b009) |
SWORD Depositor: | System Moodle |
Depositing User: | System Moodle |
Date Deposited: | 21 Feb 2024 13:10 UTC |
Last Modified: | 28 Feb 2024 10:43 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/105060 (The current URI for this page, for reference purposes) |
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