Citizen science data are increasingly used to help quantify biodiversity change. There has been a recent growth in the volume of citizen science data, particularly from participation in less-structured schemes without fixed requirements, which can attract greater numbers of observers. Data of this opportunistic nature offers opportunities to measure change for both taxa and regions which are less well-studied through formal designed surveys and monitoring. However less-structured data also presents challenges for statistical analysis, with a need to account for sources of bias and variation. This meeting will consider both challenges and future directions for measuring biodiversity change using citizen science data, featuring speakers working in the development of innovative approaches for analysing citizen science data that consider for some of the associated challenges and biases.
Alison Johnston - Outstanding analytical challenges in the analysis of citizen science data
Alex Diana - Fast Bayesian inference for large occupancy data sets, using the Polya-Gamma scheme
Michael Pocock - Getting personal with biodiversity citizen science
, University of Kent and Emily Dennis, Butterfly Conservation, on behalf of RSS Environmental Statistics Section