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Doctor of Philosophy, (Ecology)
Study Completed: 2014
College of Sciences
Predicting reintroduction outcomes using data from multiple populations
Reintroduction is a widely applied conservation tool that aims to restore locally extinct populations of native species. However, predicting reintroduction outcomes before populations are released is challenging, so reintroduction success has historically been poor. Ms Parlato developed a novel approach for predicting reintroduction outcomes, where data from multiple reintroduced populations are modelled simultaneously to identify important factors influencing population establishment and growth while accounting for random variation among sites. She then extended this multi-population approach to integrate data from multiple species. She used the resulting models to make predictions for proposed reintroductions under alternative management scenarios. Her study showed how an integrated approach to modelling reintroductions improves the information available to managers, providing guidance about site suitability and appropriate management measures to improve reintroduction success.
Professor Doug Armstrong
Dr John Innes
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Last updated on Tuesday 04 April 2017