International Journal of Marine Science, 2025, Vol.15, No.6, 287-291 http://www.aquapublisher.com/index.php/ijms 289 These variables were extracted at a 3-hour resolution, interpolated where necessary, and matched to the timing and location of citizen observations. 2.3 Displacement modeling process The PDT simulation applies a simplified particle advection model in which each sighting is treated as a release point for a virtual jellyfish swarm. The swarm is then projected forward using a composite vector equation: D = αW + βC + γV + δT Where: D is the displacement vector; W = wind vector; C = current vector; V = wave vector; T = temperature gradient; α–δ are weighted coefficients reflecting the relative influence of each factor. In the absence of AI, coefficients were manually calibrated based on observational alignment with bloom progression over time. Each sighting generated a prediction envelope, producing a forward simulation of likely jellyfish distribution for the following 1~5 days. 2.4 Limitations and assumptions This pilot version of PDT assumes passive drift behavior for jellyfish swarms and does not account for: Vertical migration patterns (Malul et al., 2024) (e.g. diel movement (Hays et al., 2012)); Active swimming behavior in some species; Biological factors like reproduction or bloom collapse; Coastal geomorphology (e.g. barriers, eddies, bathymetric influence). In addition, the current approach is deterministic and not probabilistic, which may limit its precision during periods of highly variable weather. 3 Results To evaluate the feasibility of the Predictive Displacement Theory (PDT) as a forecasting framework, we retrospectively applied its core principles to the extensive blooms of Pelagia noctiluca that spread through the Aegean Sea in the Corinthian Gulf between 2020 and 2023. These blooms were among the most persistent and widely reported in recent Mediterranean history, significantly impacting tourism, fisheries, and public safety across coastal regions of Greece. 3.1 Observation dataset Over 150 georeferenced Pelagia noctiluca observations were retrieved from the Facebook Group “Jellyfish in Greece” and iNaturalist platform, concentrated in the summer months (June to September) from 2021 to 2022. These included user-submitted photos and estimated abundances along northern and southern shores of the Corinthian Gulf. Sightings showed clear temporal clustering, often appearing in bursts following periods of sustained northerly winds and calm sea states. 3.2 Environmental drivers Environmental data collected from Windy.com revealed recurring meteorological patterns during peak bloom events: Northerly winds exceeding 20 km/h sustained for 24~48 hours. Weak east-to-west surface currents within the semienclosed Gulf. Warm sea surface temperatures exceeding 25 °C. Low wave energy in the southern coastline areas. These conditions were considered favorable for jellyfish drift from the south-eastern coasts toward south-western regions, particularly from Kiato to Derveni. 3.3 Forecasting simulation Using the PDT model in a manual, rule-based mode (without AI), jellyfish sightings were treated as initial displacement nodes. Based on contemporaneous wind, current, and wave data, forward trajectories were simulated for 5-day intervals during peak bloom periods. Key outcomes include: Southward movement predictions aligned with observed bloom locations in 2021 and 2022 with up to 90% spatial accuracy over 5-day windows. The strongest predictive alignment occurred during episodes of northerly winds combined with low wave heights (<0.8 m), which facilitated passive surface drift. Areas such as
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