This virtual meeting, organised by the Environmental Statistics Section, took place on Tuesday 22 June 2021. The speakers were Alison (Ali) Johnston, Cornell University; Michael Pocock, CEH; and Alex Diana, University of Kent.
Ali’s talk, titled 'Outstanding analytical challenges in the analysis of citizen science data', introduced and discussed a number of outstanding challenges when dealing with citizen science, or community science as it is known in the US, data. Examples included issues with the data collection, such as reporting bias and spatial bias, and with the data analysis, such as computational challenges when dealing with increasingly larger data sets.
Michael’s talk, titled 'Getting personal with biodiversity citizen science', discussed aspects of volunteer-engagement. He talked about the importance of understanding people’s behavior and patterns of engagement with citizen science, and how bringing this knowledge into the development of citizen science supports its analysis. He showed how their current NERC-funded project, DECIDE, is aiming, through co-design with recorders, to tackle some of the biases discussed in Ali’s talk.
Finally, Alex’s talk, 'Fast Bayesian inference for large occupancy data sets, using the Polya-Gamma scheme', introduced a new modelling framework for occupancy data that is considerably faster than existing Bayesian modelling approaches, while also accounting for spatio-temporal autocorrelation between sites. He demonstrated the new model using simulated as well as real data and introduced ideas of checking model-fit for such models.
Author
Eleni Matechou chairs the Environmental Statistics section.