What is citizen science?
Citizen science is scientific research carried out with the participation of the public. In ecology, it usually involves members of the public submitting data on species and habitats to a central database. The resulting databases have a wider scope, both geographically and of species covered, than is possible in surveys carried out by professionals. There is a broad range of citizen science projects, from structured designed surveys such as the Breeding Bird Survey to those that are unstructured and encourage broader participation, for example iNaturalist. Citizen science is also called ‘community science’ or ‘participatory science’.
Citizen science also includes situations in which the public submit photos for automatic identification by algorithms or experts, for example Citizen Fins. Alternatively, there are projects in which members of the public identify species that are collected by scientists, for example Snapshot Serengeti or the Iberian Camera Trap Project.
Citizen science projects provide a huge and valuable amount of data, however they also present challenges to the statistician because the data they generate can be subject to a range of biases. These biases can arise from the sites chosen by observers, the weather conditions, the expertise of the observers, the difficulty of identifying species, etc. Sophisticated modelling methods are usually needed to unlock the huge potential of citizen science databases for monitoring population and biodiversity trends.
What species are these methods used for?
Citizen science is important because of the applicability of the approach to a very wide range of taxa and species. Citizen scientists often have considerable skills in identifying species, including microscopic examination of samples, and they can also send away samples for genetic identification.
Who in CREEM works on these methods?
A few relevant publications by CREEM staff
Ball, S.G., Morris, R.K.A., Buckland, S.T. and Glennie, R. 2021. Understanding the complexity of data compiled by recording schemes. British Journal of Entomology and Natural History 34, 101-116.
Buckland, S.T. and Johnston, A. 2017. Monitoring the biodiversity of regions: key principles and possible pitfalls. Biological Conservation 214, 23-34.
Buckland, S.T., Yuan, Y. and Marcon, E. 2017. Measuring temporal trends in biodiversity. Advances in Statistical Analysis 101, 461-474.
Harrison, P.J., Buckland, S.T., Yuan, Y., Elston, D.A., Brewer, M.J., Johnston, A. and Pearce-Higgins, J.W. 2014. Assessing trends in biodiversity over space and time using the example of British breeding birds. J. App. Ecol. 51, 1650-1660.
Harrison, P.J., Yuan, Y., Buckland, S.T., Oedekoven, C.S., Elston, D.A., Brewer, M.J., Johnston, A. and Pearce-Higgins, J.W. 2016. Quantifying turnover in biodiversity of British breeding birds. J. App. Ecol. 53, 469-478.
Studeny, A.C., Buckland, S.T., Harrison, P.J., Illian, J.B., Magurran, A.E. and Newson, S.E. 2013. Fine-tuning the assessment of large-scale temporal trends in biodiversity using the example of British breeding birds. J. App. Ecol. 50, 190-198.
Swallow, B.T., Buckland, S.T., King, R. and Toms, M.P. 2016. Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: an application to a study of birds visiting gardens in winter. Biometrical Journal 58 SI, 357-371.
Swallow, B.T., Buckland, S.T., King, R. and Toms, M.P. 2019. Assessing factors associated with changes in the numbers of birds visiting gardens in winter: are predators partly to blame? Ecology and Evolution 9, 12182-12192.
Johnston A, Matechou E, Dennis EB. (2023) Outstanding challenges and future directions for biodiversity monitoring using citizen science data. Methods in Ecology and Evolution 14(1): 103-116.
Johnston A, Hochachka WM, Strimas-Mackey ME, Ruiz Gutierrez V, Robinson OJ, Miller ET, Auer MT, Kelling ST, Fink D. (2021) Analytical guidelines to increase the value of community science data: an example using eBird to estimate species distributions. Diversity and Distributions 27(7): 1265–1277.