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| Funder | Natural Environment Research Council |
|---|---|
| Recipient Organization | University of Southampton |
| Country | United Kingdom |
| Start Date | Sep 24, 2023 |
| End Date | Mar 25, 2027 |
| Duration | 1,278 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2893495 |
Many wildlife species have been pushed into Earth's few remaining areas still unmodified by human activities, at the edge of existence. Advances in the capabilities of Uncrewed Aerial Vehicles (UAVs), remotely operated camera and acoustic technologies, and big-data analysis by machine learning, now offer opportunities to survey otherwise inaccessible areas and develop robust datasets for populations of conservation concern, which are often cryptic species.
This technology promises - but has not yet delivered on its potential - to count animals too rare for foot patrols and too cryptic for satellite imagery, to follow individual animals without disturbing them, and to quantify forest biodiversity and hunting frequency from soundscapes1 - all complex problems insoluble by direct observation.
Your project will develop and test methodologies for evaluating this promise. You will trial newly developed equipment and collect field data relevant to conservation management of snow leopards in Kazakhstan (IUCN Red Listed as Vulnerable), and/or scimitar-horned oryx (Regionally Extinct), addax (Critically Endangered) and slender-horned gazelles (Endangered) in Tunisia.
By the end of this project, you will have added to global knowledge on value and limits of conservation technology, to projections for population trajectories of endangered mammals, and to understanding of causes of population declines.
University of Southampton
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