The work of C.B.H. was supported by a Brandeis University Provost Research grant. The work of D.F. was supported by the European Union’s Horizon 2020 Research And Innovation Programme EU-Citizen.Science project (under grant agreement number 824580). The work of F.D. was supported by the European Union’s Horizon 2020 Research And Innovation Programme INTAROS, CAPARDUS and FRAMEwork projects (under grant agreement numbers 727890, 869673 and 862731), and the Danish Agency for Science and Higher Education through the UArctic Thematic Network on Collaborative Resource Management. The work of G.H. was supported by the European Union’s Horizon 2020 research and innovation programme EU-Citizen.Science and FRAMEwork projects (under grant agreement numbers 824580 and 862731). The work of J.M.H. was supported by the AFRI Postdoctoral Fellowship grant 2020-67034-31766 from the USDA National Institute of Food and Agriculture. The work of J.P. was supported by the European Union’s H2020 Research And Innovation Programme Cos4Cloud project (under grant agreement number 863463); J.P. also acknowledges the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). The work of M.H. was supported by the European Union’s ERC Advanced Grant project ‘European Citizen Science: Analysis and Visualisation’ (under grant agreement number 694767); and the European Union’s Horizon 2020 Research And Innovation Programme EU-Citizen.Science and TIME4CS projects (under grant agreement numbers 824580 and 101006201). The work of M.T. was supported by the European Union’s Horizon 2020 Research And Innovation Programme MINKE project (under grant agreement number 101008724). The work of P.-Y.H. was supported by P. Stephens, Department of Biosciences, Durham University, UK; the Belmont Community School, Durham, UK; the Durham Wildlife Trust, Durham, UK; the United Kingdom Heritage Lottery Fund (grant numbers OH-14-06474, OM-21-00458 and RH-16-09501); the British Ecological Society; the United Kingdom Economic and Social Research Council Impact Acceleration Account, Durham University (grant numbers TESS–ESLE2012 and 030-15/16, and a Doctoral Scholarship); the United Kingdom Natural Environment Research Council (NE/R008485/1); the European Food Safety Authority (grant numbers OC/EFSA/ALPHA/2016/01–01 and OC/EFSA/AMU/2018/02); a HMP and YOI Deerbolt Operational Innovation Award, and the Royal Society (grant number PG\S2\192047)

Citizen science is an increasingly acknowledged approach applied in many scientific domains, and particularly within the environmental and ecological sciences, in which non-professional participants contribute to data collection to advance scientific research. We present contributory citizen science as a valuable method to scientists and practitioners within the environmental and ecological sciences, focusing on the full life cycle of citizen science practice, from design to implementation, evaluation and data management. We highlight key issues in citizen science and how to address them, such as participant engagement and retention, data quality assurance and bias correction, as well as ethical considerations regarding data sharing. We also provide a range of examples to illustrate the diversity of applications, from biodiversity research and land cover assessment to forest health monitoring and marine pollution. The aspects of reproducibility and data sharing are considered, placing citizen science within an encompassing open science perspective. Finally, we discuss its limitations and challenges and present an outlook for the application of citizen science in multiple science domains

20 pages, 3 figures, 4 tables, supplementary information https://doi.org/10.1038/s43586-022-00144-4

Peer reviewed