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• W4295093106 abstract "Jellyfish swarms have a direct negative impact on human enterprise, specially on places dependent on the sun and beach economy. The local economy and the health of bathers may be at risk from the emergence of these gelatinous organisms. Economic losses can be mitigated by monitoring the occurrence of jellyfish on the coast. Due to the lack of jellyfish data, environmental citizen science is presented as an alternative for data collection. In this study, fuzzy logic-based models have been used to modelize the knowledge from citizen comments collected by the Infomedusa app. The effect of local climatological factors such as wind speed and direction on the incidence of jellyfish on the coast was studied. The fuzzy logic-based models showed that winds perpendicular to the coast lead to a higher occurrence of jellyfish swarms in central and eastern Malaga, while winds parallel to the coast have a greater influence in the westernmost coasts. Wind speed has a different effect on jellyfish incidence depending on the study area and wind direction. Data extracted from the Infomedusa app can help to address the historical scarcity of scientific data on jellyfish. This app presents an opportunity for future studies to expand the knowledge about the occurrence of these organisms on the coasts and may contribute to the prediction of onshore arrival. • Citizen science combined with fuzzy logic makes it possible to deal with the historical scarcity of jellyfish data. • Wind speed and direction play a fundamental role in understanding the appearance of jellyfish on the coast of Malaga. • In the western Costa del Sol, parallel winds favour the appearance of jellyfish. • In the central and eastern Costa del Sol, the winds perpendicular to the coast favour the appearance of jellyfish." @default.
• W4295093106 created "2022-09-10" @default.
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• W4295093106 date "2022-10-01" @default.
• W4295093106 modified "2023-10-16" @default.
• W4295093106 title "Estimation of jellyfish abundance in the south-eastern Spanish coastline by using an explainable artificial intelligence model based on fuzzy logic" @default.
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• W4295093106 doi "https://doi.org/10.1016/j.ecss.2022.108062" @default.
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