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

With mounting global concerns about jellyfish outbreaks, monitoring their occurrence remains challenging. Tapping into the wealth of digital data that internet users share online, which includes reports of jellyfish sightings, may provide an alternative or complement to more conventional expert-based or citizen science monitoring. Here, we explore digital footprints as a data source to monitor jellyfish outbreaks along the Israeli Mediterranean coast. We compiled jellyfish sighting data for the period 2011-2022 from multiple platforms, including leading social media platforms, searches in the Google search engine, and Wikipedia page views. Employing time series analysis, cross-correlation, and various evaluation metrics for presence/absence data, we compared weekly data from three sources: digital footprints, citizen science, and traditional expert-based field monitoring. Consistent seasonal patterns emerge across datasets, with notable correlations, particularly in jellyfish abundance. The cross-correlation between digital footprint and citizen science data exceeds >0.7, with Twitter and Instagram showing the highest correlation. Citizen science data often precedes digital footprints by up to one week. Correlation with traditional, expert-based field monitoring is limited as a result of limited data availability. Digital footprints demonstrate substantial agreement with the other data sources regarding jellyfish presence/absence and major outbreaks, especially for data from Wikipedia, Twitter, and Instagram. Overall, we highlight digital footprint data as a reliable, cost-effective tool for passive monitoring of jellyfish outbreaks, which can aid characterization in data-scarce coastal regions, including retrospective assessment. Transferring and scaling up the proposed approach should consider data accessibility as well as platform relative popularity and usage in the regions under investigation.