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Citizen science in environmental and ecological sciences

Nature Reviews Methods Primers volume 2, Article number: 64 (2022) Cite this article

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Abstract

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.

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Fig. 1: Stages of designing and implementing a citizen science project in ecology and environmental sciences.
Fig. 2: Stylized citizen science quality assurance process for quantitative measures of species abundance.
Fig. 3: Best practice for publishing outputs from a citizen science project.

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Change history

  • 10 November 2022

    In the version of this article initially published, the name of a peer reviewer, Corlia Meyer, was misspelled as “Cornelia” in the reviewer acknowledgements, and has now been amended in the HTML and PDF versions of the article.

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Acknowledgements

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).

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Authors and Affiliations

  1. Novel Data Ecosystems for Sustainability Research Group, Advancing Systems Analysis Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    Dilek Fraisl & Gerid Hager

  2. Centre d’écologie et des sciences de la conservation, Muséum national d’Histoire naturelle, Paris, France

    Baptiste Bedessem

  3. Faculté de droit, Université de Namur, Namur, Belgium

    Baptiste Bedessem

  4. Citizen Science Lab, Leiden University, Leiden, Netherlands

    Margaret Gold

  5. Department of Mechanical Engineering, University of Bath, Bath, UK

    Pen-Yuan Hsing

  6. Nordic Foundation for Development and Ecology (NORDECO), Copenhagen, Denmark

    Finn Danielsen

  7. Department of Biology, Brandeis University, Waltham, MA, USA

    Colleen B. Hitchcock

  8. Ornamental Plant Pathology, Department of Plant Pathology, Puyallup Research and Extension Center, Washington State University, Puyallup, WA, USA

    Joseph M. Hulbert

  9. Environmental and Sustainability Participatory Information Systems Group, Institute of Marine Sciences (ICM-CSIC), Barcelona, Spain

    Jaume Piera

  10. Electron Microscopy Science Technology Platform, The Francis Crick Institute, London, UK

    Helen Spiers

  11. Departamento de Biologia Marina, Facultad Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile

    Martin Thiel

  12. Millennium Nucleus Ecology and Sustainable Management of Oceanic Island (ESMOI), Coquimbo, Chile

    Martin Thiel

  13. Centro de Estudios Avanzados en Zonas Áridas (CEAZA), Coquimbo, Chile

    Martin Thiel

  14. Department of Geography, University College London (UCL), London, UK

    Mordechai Haklay

Authors
  1. Dilek Fraisl
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  2. Gerid Hager
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  3. Baptiste Bedessem
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  4. Margaret Gold
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  5. Pen-Yuan Hsing
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  6. Finn Danielsen
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  7. Colleen B. Hitchcock
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  8. Joseph M. Hulbert
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  9. Jaume Piera
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  10. Helen Spiers
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Contributions

D.F. and G.H. contributed equally as first authors. B.B., M.G. and P.-Y.H. contributed equally as second authors. Introduction (D.F., G.H. and M.G.); Experimentation (D.F., G.H., C.B.H., H.S. and M.H.); Results (D.F., G.H., B.B. and J.M.H.); Applications (D.F., G.H., F.D., J.M.H., J.P., M.T. and P.-Y.H.); Reproducibility and data deposition (D.F., G.H. and P.-Y.H.); Limitations and optimizations (D.F., G.H., B.B., J.P., and M.H.); Outlook (D.F., G.H., M.G. and P.-Y.H.); Overview of the Primer (D.F., G.H. and M.H.).

Corresponding author

Correspondence to Dilek Fraisl.

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Nature Reviews Methods Primers thanks Finn Arne Jorgensen, Corlia Meyer, Kirsten Silvius and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

AfriAlliance Knowledge Hub: https://afrialliance.org/knowledge-hub

Atlas of Barcelona Biodiversity: https://ajuntament.barcelona.cat/atlesbiodiversitat/en/

Australian Citizen Science Association: https://citizenscience.org.au/

CERN Open Hardware Licences: https://ohwr.org/project/cernohl/wikis/Documents/CERN-OHL-version-2

CesiumJS open source JavaScript library: https://cesium.com/platform/cesiumjs/

choosealicense.com: https://choosealicense.com/

Cientificos de la Basura: http://www.cientificosdelabasura.cl/en/

Citizen Science Africa Association: https://www.usiu.ac.ke/citsci-africa-association/

CitizenScience.Asia: http://www.citizenscience.asia/

Citizen Science Association in the USA: https://citizenscience.org/

Citizen Science Center at the University of Zurich: https://citizenscience.ch/en/

Citizen Science Global Partnership: http://globalcitizenscience.org/

CitSci.org: https://www.citsci.org

Community-based Monitoring Library: https://mkp28.wixsite.com/cbm-best-practice

Cos4Cloud project: https://cos4cloud-eosc.eu/

Creative Commons: https://creativecommons.org/about/cclicenses

CWDAT open source tool: https://spatial.wlu.ca/cwdat/

Darwin Core: https://dwc.tdwg.org/

Data Visualization Overlay: https://www.spotteron.net/blog-and-news/making-data-meaningful-data-visualization-overlay-in-citizen-science-apps-on-the-spotteron-platform

Dryad: https://datadryad.org/stash/

EU-Citizen.Science: https://eu-citizen.science/

European Citizen Science Association: https://ecsa.citizen-science.net/

European Environment Agency’s Marine Litter Watch: https://www.eea.europa.eu/themes/water/europes-seas-and-coasts/assessments/marine-litterwatch/data-and-results/marine-litterwatch-data-viewer

European Open Science Cloud: https://eosc-portal.eu/

Forest Health Watch program: https://foresthealth.org/

FotoQuest Go: http://fotoquest-go.org/

Global Earth Challenge Marine Litter Data Integration Platform: https://globalearthchallenge.earthday.org/datasets/data-earth-challenge-integrated-data-plastic-pollution-mlw-mdmap-icc-2015-2018/explore?location=2.132530%2C2.357206%2C1.89

Great Southern BioBlitz: https://www.inaturalist.org/projects/great-southern-bioblitz-2021-umbrella

iNaturalist: https://github.com/inaturalist/

Iberoamerican Network of Participatory Science (RICAP): http://cienciaparticipativa.net/la-ricap/

MammalWeb: https://www.mammalweb.org/

National Oceanic and Atmospheric Administration’s (NOAA) Marine Debris Monitoring and Assessment Project’s Accumulation Data: https://mdmap.orr.noaa.gov/

Ocean Conservancy’s International Coastal Cleanup (ICC) Trash Information and Data for Education and Solutions (TIDES) database: https://www.coastalcleanupdata.org/

OSF: https://osf.io/

Plastic Pirates: https://www.plastic-pirates.eu/

Public Lab: https://publiclab.org/

Public Participation in Scientific Research (PPSR) Core: https://core.citizenscience.org/

Registry of Research Data Repositories: https://www.re3data.org/

Safecast: https://safecast.org/

Spipoll: https://www.spipoll.org/

The Zooniverse: https://github.com/zooniverse/

URBAMAR: https://www.natusfera.org/projects/urbamar

Western Redcedar Dieback Map: https://www.inaturalist.org/projects/western-redcedar-dieback-map

Zenodo: https://zenodo.org/

Supplementary information

Glossary

Participants

A participant is a person who takes part in a citizen science project in a non-professional capacity, by helping to define its focus, gather or analyse data. Other terms used are contributor, volunteer or citizen scientist.

Lay knowledge

Lay knowledge comes from personal experience or tradition rather than formal education or professional research.

Indigenous knowledge

Understandings, skills and worldviews developed by societies with centuries to millennia of interactions with their natural surroundings, and with potential to inform decision-making about fundamental aspects of day-to-day life.

Contributory citizen science

Citizen science programmes designed by professional scientists and involving primarily non-credentialled participants contributing to data collection.

In situ

In situ refers to data that are gathered on a site, an activity that takes place locally, or an observation made at a specific location on the ground.

Opportunistic data

Opportunistic data are gathered by participants, usually while being engaged in another activity, such as taking a walk. Data collection does not follow a structured sampling design and can therefore be unevenly distributed or contain biases.

Structured/semi-structured/unstructured

Citizen science programmes may be placed along a spectrum from structured to unstructured protocols. The level of structure of a protocol is defined both by the degree of prescription in space and time of the sampling effort and by the degree of training and experience of the participants.

Community-led citizen science

Citizen science programmes involving members of the public and communities not only primarily as data collectors but also in additional stages of the research process (including identifying the question of interest, designing methodologies, interpreting data, and using data for decision-making), although professional scientists may provide advice and training.

BioBlitz

A collective activity, most often open to the public, to record biodiversity observations within a set time frame and within a defined spatial area, often also combined with expert talks and hands-on activities.

Metadata

Metadata help to identify basic information about data regarding when, where and how the data were gathered, for what purpose, what information they include and how the data quality was ensured, among others.

Bottom-up

Self-organized, people-led initiatives, often forming around matters of local concern or shared interest.

OpenStreetMap

The Wikipedia of maps — a free and open digital map of the world, created by volunteers.

Data minimization

The collection and processing of only as much data as is absolutely necessary for the purposes specified.

Citizen observatories

Community-based environmental monitoring initiatives that gather citizen science data for policymaking, and environmental management and governance.

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Fraisl, D., Hager, G., Bedessem, B. et al. Citizen science in environmental and ecological sciences. Nat Rev Methods Primers 2, 64 (2022). https://doi.org/10.1038/s43586-022-00144-4

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