Temporal trends in opportunistic citizen science reports across multiple taxa

Area of Science:

• Ecology
• Biodiversity Science
• Computational Biology

Background:

• Online platforms for species observations are vital for biodiversity monitoring.
• Analyzing opportunistic reporting data presents challenges due to lack of sampling design and temporal variations.
• Understanding reporting dynamics is key to accurately interpreting species distribution and status.

Purpose of the Study:

• To investigate temporal changes in species reporting on the Artportalen platform in Sweden.
• To decompose reporting changes into long-term trends, seasonal effects, and influences of weekdays, holidays, and weather.
• To identify how these reporting dynamics vary across different taxonomic groups.

Main Methods:

• Utilized 80 million species records from Artportalen, focusing on fungi, plants, beetles, butterflies, and birds.
• Applied time-series analysis to decompose reporting data into various temporal components.
• Examined correlations between reporting frequency and factors like weekdays, holidays, and weather variables.

Main Results:

• Significant long-term and seasonal trends in species reporting were identified across the studied taxonomic groups.
• Reporting patterns showed non-trivial changes, differing notably between fungi, plants, beetles, butterflies, and birds.
• The surge in records post-portal launch is associated with complex temporal reporting dynamics.

Conclusions:

• Temporal reporting patterns on citizen science platforms are influenced by user community behavior and platform evolution.
• These dynamics can impact the interpretation of biodiversity trends derived from such data.
• Further research into observer behavior is needed for robust ecological inference from opportunistic species data.