Big data analytics for avian ecology and conservation

Data-driven conservation requires diverse datasets in order to plan effective and efficient conservation. I will explore several datasets collated and analysed within the Cornell Lab of
Ornithology and describe how they have been used to support conservation decisions. The citizen science project eBird collects thousands of data points each day and has been  sed to derive robust species distributions across the full annual cycle and the entire Western Hemisphere at high spatial and temporal resolutions. These distributions have  informed precision conservation and large-scale prioritisations. Radar data monitors the migrating avian community, enabling insight into the weather patterns that drive migration and enabling migration forecasts, which can support conservation initiatives. Last, data from Google can tell us about how people are relating to the natural world  and which species they are most interested in. Overall, we will explore how big data and creative analytical methods can inform evidence-based conservation for bird communities