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The fate of the world’s largest carnivores: understanding declines and recoveries

Johnson, T. F. (2021) The fate of the world’s largest carnivores: understanding declines and recoveries. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00109069


Humans are reliant on biodiversity and the ecosystem services that biodiversity provides. However, the status of biodiversity is unclear, with reports of both declines and recoveries, suggesting a new complex biodiversity change narrative. Large carnivores are a perfect example of this complex narrative. On one side, there are extensive reports of declines, but more recently, some populations appear to be recovering and expanding their range. In this thesis, I use interdisciplinary approaches covering evolutionary biology, biodiversity science, data science, and social science to explore influences of biodiversity change, specifically understanding declines and recoveries in these large carnivore species. I start by introducing the current literature on biodiversity change and the status of large carnivores, highlighting weaknesses in the available methods and data. In Chapter 2, I review one of the methodological weaknesses – approaches for handling missing trait values – providing some recommendations and warnings. In Chapter 3, I addressed known data biases in large carnivore population trends and build a new dataset obtained from an extensive and systematic search of the literature for population data. In Chapter 4, I develop a trait-based model exploring environmental and anthropogenic factors influencing large carnivore population trends and describe the status of the carnivore guild. Findings show diverse factors influence population change, but that this guild has and will remain relatively stable between 1970 and 2050. These results provide optimism for the status of large carnivores, and biodiversity more generally. However, I suspect our model failed to capture important characteristics on human perceptions and tolerances of carnivores, which could impact their population status. As a result, in Chapter 5, I develop a machine learning text classifier to measure public opinions of nature from social media. This, or tools like it, could be effective at capturing these previously undetected tolerance features at a global scale. Finally, chapter 6 summarises the collective thesis findings and offers my thoughts on the status of large carnivores and biodiversity change research.

Item Type:Thesis (PhD)
Thesis Supervisor:Gonzalez-Suarez, M., Isaac, N. J. B. and Paviolo, A.
Thesis/Report Department:School of Biological Sciences
Identification Number/DOI:
Divisions:Life Sciences > School of Biological Sciences
ID Code:109069

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