Importance of Citizen Science in Adaptive Management

Citizen Science

What is Citizen Science?

• Engages non-professionals in authentic scientific research
• Ranging from long-standing, large scale projects to more personalized research experiences

Categories of CS

1. Contributory
2. Collaborative
3. Co-creative

• Citizens might be engaged to differing degrees within each category.
• There is no ‘right’ level of participation

CS keeps coming up….websites, books, articles, now a conference, now a whole CS month

Four Main Questions

1. What is citizen science?

• Engages non-professionals in authentic scientific research
• Ranging from long-standing, large scale projects to more personalized research experiences
• Partnerships between amateur and natural scientists
• These projects guide public participation in ecological research topics and studies of abiotic factors
• Efforts involved collections of data across temporal and geographic scales
• Process that connects people to science
• Started about 20 years ago with the opening up of the internet and democratization of knowledge
• Tends to involve the collection of data across large temporal and spatial scales

1. What opportunities does it offer?

• Development of long term relationships between participants and organisations (lead to long term monitoring)
• Allows for layering question driven research into existing monitoring projects
• Combining historical CS data sets with current observations to gain insight into ecological impacts
• Can develop a much broader dataset covering much larger spatial and temporal scales
• Data collection no longer spatially bound by where researchers are  (global issues)
• Creates a platform for sharing scientific monitoring data with the public
• Opens up the possibility of engaging with and sharing with more ethnically & culturally diverse participants
• In community setting – opportunities to engage entire families, not just individuals  (multi generational impact)
• Generates ecological knowledge and elevates public understanding and support for citizen science
• Allows for community based projects to be initiated as CS identifies local issues and needs
• It builds earth stewardship as it educates the local and provides tangible science for the communities to utilize in the future
• Promotes dialogue between public and scientific community through the use of mobile apps and social media in relation to citizen science
• Allows for multi-disciplinarity as CS projects often cross borders of various scientific disciplines

1. How can quality data be ensured?

• Educating citizen scientists about what they are doing and why.
• Offering training and on-going support
• Larger data sets give greater precision, iron out anomolies (therefore aim for larger databases)
• Can create ‘smart filters’ for obviously incorrect data AND find ways to either flag inaccurate data gatherers or anomalous data.
• Can use verifying tools such as photographs (SABAP example)
• Ongoing interactions with participants (lots of communication)
• Create really simple data collection protocols
• Create reward systems for good work  (competitions, certificates)
• Educational games and historical reports
• Also an increase in the technology used to collect data
• Stringent criteria to ensure data accuracy
• The use of floating forests → multiple opinions of one piece of data or subject
• Offer opportunities to educate the public at every step in the project
• Identify common priority areas and adopt a clarity towards the aims of the project
• Mobile apps and SMS services which acts as data collection mechanisms or data storage mechanisms

1. How can Participation be sustained

1. Easy, fun and social (games and challenges)
2. Working closely with target audiences
3. Creating an atmosphere of shared values
4. Partnerships with local organisations
5. Incentives such as compensation and recognition
6. Communication between staff and volunteers
7. Mainstream the enjoyment opportunities for participants
8. Make sure your citizen science project and methods are user friendly
9. Tap into growing use of social media to spread support for citizen science projects
10. Data is openly accessible to the public
11. Expert feedback to the public

Ethical concerns of Citizen Science

1. Disturbance to environment through collection
2. Inclusion vs exclusion → how do you choose your citizen scientists
3. When TEK is invoked or claimed, how do you determine who has the right to the knowledge
4. Citizen science may attempt to change local traditional lifestyles to solve the problem when the life styles of these people is actually not the main cause
5. Must ensure that projects are sustainable and benefit the community before and after the project
6. Another is issue is the jargon → the project needs to respect the language of the communities it requires to volunteer
7. Attribution of credit and authorship is a major concern → CS must adopt a model which fairly and thoroughly acknowledges participants and their roles in the study