From citizen science data to demographic information, exploring the potential of the global eBird project

The eBird project (ebird.org/home) is a global initiative bringing together the power of citizen science with the academic community. The freely available app gives participants of any experience level the opportunity to add to the data collected on the world’s bird species. The growing contribution rate to the database, over 100 million bird sightings are added every year, offers incredible statistical opportunities to offer data-driven progress in science, conservation and education.

The scale and volume of the data available offer many exciting statistical opportunities. This PhD project would look to explore and develop analytical approaches to produce detailed and reliable ecological information. Potential avenues of research may include:

•           Considering statistical tools and techniques that fully describe all sources of error and variability from raw data collection, machine learning and data cleaning, through to quantifying and visualising the uncertainty from statistical analyses;

•           Integrating eBird data with more structured demographic data to estimate population dynamics and make inference from large-scale patterns to mechanistic processes;

•           Exploring changes in the observation process over time and potential drivers behind those changes, for example, the impact of COVID on the sampling distribution, or improvements to identification tools;

•           Investigating the impact of survey effort and urban bias on the coverage and availability of data across the whole geographic area of interest;

•           Identifying long-term patterns or evolving trends in population behaviour, e.g. breeding, phenology, environmental factors, changes in location preferences.

Suitable applicants should have a strong statistical background. Desirable experience would include: experience with programming (R/python); experience with advanced statistical methods or machine learning tools; experience dealing with large datasets; an interest in ecology or birds.

For more information, including how to apply, please see this document (pdf file): Postgraduate Opportunities in Statistics. See also the School’s Postgraduate Research web page.