Monitoring jellyfish outbreaks along Israel's Mediterranean coast using digital footprints

Area of Science:

• Marine Biology
• Ecology
• Data Science

Background:

• Jellyfish outbreaks pose global challenges, necessitating effective monitoring strategies.
• Traditional monitoring methods are often resource-intensive and limited in scope.
• Digital data offers a potentially vast, underutilized resource for ecological monitoring.

Purpose of the Study:

• To evaluate the efficacy of digital footprints as a tool for monitoring jellyfish outbreaks.
• To compare digital footprint data with citizen science and expert-based monitoring.
• To assess the reliability and cost-effectiveness of using online data for jellyfish surveillance.

Main Methods:

• Compiled jellyfish sighting data from 2011-2022 from social media, Google searches, and Wikipedia page views.
• Employed time series analysis and cross-correlation to compare weekly data from digital footprints, citizen science, and expert monitoring.
• Utilized presence/absence data evaluation metrics to assess agreement between datasets.

Main Results:

• Consistent seasonal patterns in jellyfish occurrences were observed across all data sources.
• High cross-correlation (>0.7) was found between digital footprint data and citizen science data, particularly from Twitter and Instagram.
• Digital footprints showed substantial agreement with other sources for presence/absence and major outbreaks, especially Wikipedia, Twitter, and Instagram data.

Conclusions:

• Digital footprints provide a reliable and cost-effective passive monitoring tool for jellyfish outbreaks.
• This approach can enhance characterization in data-scarce coastal areas and aid retrospective assessments.
• Future implementation requires consideration of data accessibility and platform popularity in target regions.