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  Using long-term data to secure the future of a species with minimal management?


   School of Animal, Rural and Environmental Sciences

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  Dr Simon Tollington  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

The island of Mauritius is globally recognised as a hotspot of successful species conservation. Thanks to the efforts of the Mauritian Wildlife Foundation, the Government of Mauritius, Durrell Wildlife Conservation Trust and a host of collaborating partners, at least five species of endemic bird have been saved from certain extinction. 

The Mauritius or ‘Echo’ parakeet is perhaps the most acutely studied. Its recovery from a population size of fewer than 20 individuals in the 1980s to more than 150 breeding pairs and 800 individuals in 2020 has been documented in remarkable detail, owing to an intensive conservation management and monitoring initiative. For ~30 years, each known nest-site has been monitored annually and unique leg-rings fitted on all newly hatched chicks resulting in a database that describes more than 1500 breeding attempts and a genetically supported studbook detailing nearly 5000 individuals. The data doesn’t stop there; the recovery of this species has continued despite the outbreak of an infectious disease. More than 1200 individuals have been tested for Beak and Feather Disease Virus (BFDV) and more than 500 viral DNA sequences exist from a bank of stored blood samples. 

Population recovery is largely due to the provision of artificial nest-boxes and supplemental food but as a consequence of success, field biologists are no longer able to manage this growing population so intensively. Withdrawing all management cannot be an option however, not least because of the ongoing threat of infectious disease, but how can managers use this remarkable long-term data to design minimal management strategies to monitor critical population parameters whilst also serving as an early-warning system of population decline? 

This project will use extensive, individual-based datasets and re-sightings data collected over 30 years to initially construct advanced Capture-Mark-Recapture models of key demographic parameters for this species. Predictive population models will help to answer fundamental questions; what are the environmental, management and demographic factors that limit individual survival? How does viral infection impact survival? 

How can we use the answers to these questions to devise minimal management strategies? How many nest-sites should we monitor to give a representative view of the population as a whole? Which nest-sites should we monitor and how often? What is the minimum number of nest sites we need to monitor in order to recognise a notable reduction in productivity or survival? 

What management tools do we need to maintain to ensure a viable population and which can we afford to withdraw? 

Biological Sciences (4) Information Services (20) Mathematics (25)

Where will I study?

 About the Project