Henriques, Sérgio da Silva;
(2023)
Protecting the unknown: Towards assessing extinction risk in megadiverse groups.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
The ongoing biodiversity crisis is one of today's most challenging and pressing global issues. Under fears that humans are currently causing the 6th mass extinction of Earth’s history, with global consequences at all levels of society, international policy targets have been set to halt biodiversity loss. This includes the United Nations’ Sustainable Development Goals and the Convention on Biological Diversity’s Aichi Targets. In order to measure progress towards these targets, several biodiversity indicators have been proposed, one of the most relevant of which is the Red List Index (RLI). In this thesis, I revise current methods to detect and monitor the extinction risk of megadiverse groups via the sampled approach to the RLI (sRLI). In the first chapter, I introduce the biodiversity crisis, current policy targets set to stop it, and the biodiversity indicators that inform them while reviewing the constraints of the currently available IUCN Red List data, focusing on the limitations of a non-random sample. In chapter 2, I revise a random sampled approach to the RLI in light of recent biodiversity targets, and using a wider dataset than originally available, I demonstrate that much smaller sample sizes than previously proposed can be representative of a group's overall trend. In chapter 3, I investigate how samples currently set to detect RLI trends can also represent a group’s overall percentage of threatened species, which I propose could be used as a new biodiversity indicator. In chapter 4, I implemented the sRLI to assess the extinction risk of a megadiverse case study group, the poorly known spiders (order Araneae), where I found data deficiency (DD) to be one of the main obstacles to the implementation of the sRLI. In chapter 5, I tackle taxonomy as one of the main reasons for DD in megadiverse groups. I propose several paths to reduce potential bias caused by taxonomy under a sRLI approach and taxonomically revise several species of a case study group, the Eresus and closely related Loureedia genus. In chapter 6, I synthesise my findings and discuss potential solutions to overcome the main issues found when implementing this protocol.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Protecting the unknown: Towards assessing extinction risk in megadiverse groups |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2022. 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 |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10184551 |
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