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Title: Species conservation in the era of digital big data
Author: Mittermeier, John C.
ISNI:       0000 0004 8507 872X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2020
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The Earth is in the midst of a global biodiversity crisis. Populations of plants and animals are declining dramatically, and thousands of species are predicted to go extinct in the coming century. This thesis explores how a new technological resource, digital 'big data,' can help conservationists combat this challenge. Big data has led to revolutionary advances in multiple fields but until recently has received limited attention in conservation. I focus on one aspect of big data, the data generated by people's activity online, and on one type of conservation, the conservation of species. I develop methods to access and interpret data related to people's interest in species using a prominent online platform, Wikipedia, and identify methodological challenges associated with this. I highlight the ability of Wikipedia pageviews to address questions of public interest in species across broad social and geographic scales and over vast numbers of online interactions. After developing methods to access and interpret relevant Wikipedia data, I explore patterns that these data reveal. I identify the biological traits of species that influence public attention and highlight the importance of seasonal and geographic patterns in determining public interest in species. I find that the presence and abundance of a species in a region is a significant predictor of its public interest across temporal and geographic scales. I conclude by identifying ways in which the insights revealed through these methods can be applied to conservation. Specifically, I argue that online data can provide awareness as to why people prefer, and thus are more inclined to conserve, some species rather than others; be used to systematically identify species of high interest at global and regional scales; monitor temporal and spatial variations in public attention; and, in some cases, track the distribution and abundance of species. I conclude that online big data are a valuable compliment to existing conservation methods. Knowing how to access and interpret these data should be part of every conservationist's tool kit in the twenty-first century.
Supervisor: Grenyer, Richard Sponsor: Wilfrid Knapp Scholarship
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available