How training citizen scientists affects the accuracy and precision of phenological data

Area of Science:

• Ecology
• Citizen Science
• Biodiversity Monitoring

Background:

• Phenological monitoring is crucial for predicting species interactions and biodiversity changes.
• Citizen scientists are vital for collecting phenological data due to the need for frequent observations.
• Concerns exist regarding the accuracy and precision of citizen science data, with limited comparisons of trained versus untrained observers.

Purpose of the Study:

• To assess how experts, trained citizen scientists (repeated observations), and untrained citizen scientists (annual observations) differ in quantifying phenological changes.
• To evaluate the impact of observer training and observation frequency on the accuracy and precision of phenological data.
• To identify potential biases introduced by different citizen science data collection methods.

Main Methods:

• Compared phenological data on flower and fruit abundance of American mountain ash (Sorbus americana) and associated arthropods.
• Utilized three observer types: experts, trained citizen scientists making repeated observations, and untrained citizen scientists making annual observations.
• Conducted study in Acadia National Park, Maine, USA.

Main Results:

• Trained citizen scientists, more than untrained ones, tended to over- or under-estimate abundances.
• This led to precise but inaccurate characterizations of phenological patterns.
• Repeated observations introduced a bias, reducing the independence of observations and suggesting a learning effect.

Conclusions:

• One-off observations by citizen scientists may yield data as good as or better than repeated observations by trained individuals.
• Citizen science programs should prioritize attracting a large number of observers, even for single observations.
• Developing user-friendly data sheets is essential for improving phenology data quality.