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Unravelling ecological dynamics at a macro scale: application of hierarchical models

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If you have a question about this talk, please contact Dr. Belinda Gallardo .

Understanding and predicting ecological dynamics at a macro scale is crucial for the conservation of global biodiversity. But macro-scale ecological studies usually rely on data, such as volunteer-based monitoring data or natural history collections, which tend to have inherent problems that need to be dealt with first. Hierarchical Bayesian models provide a robust framework for tackling such problems in macro-scale ecological data. In this talk, I will introduce the potential of hierarchical Bayesian models using two examples of actual applications in my own work: estimating long-term phenological changes in British plants and explaining varying effectiveness of organic farming in Japanese rice fields at a broad scale.

This talk is part of the Ecology Lunchtime Series series.

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