Abstract
In the context of the global seafood industry, the Azores archipelago (Portugal) plays a pivotal role due to its vast maritime domain. This study employs complex network analysis techniques to investigate the dynamics of Azores fisheries, using time series data converted into networks. We uncover associations between Tunas and specific islands, consistent links among fish classifications, and identify other pivotal nodes within the fishing network. Remarkably, nodes with high degrees and high betweenness centrality provide crucial insights into the fishing ecosystem. This study highlights the value of network analysis for understanding fisheries complexities and offers insights into sustainable management and the preservation of marine ecosystems. It also emphasizes the urgency for ongoing research and data collection to enrich our understanding of this multifaceted domain.
B. Nogueira and A. Torres—Contributed equally to this work.
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Acknowledgements
We acknowledge the LOTAÇOR, S.A., a regional public company responsible for the fish auctions and fisheries landings statistics, and João Santos (OKEANOS - UAc), which manages the LOTAÇOR/OKEANOS-UAC fishing landings database.
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Nogueira, B., Torres, A., Moniz, N., Menezes, G.M. (2025). Dynamics of Fisheries in the Azores Islands: A Network Analysis Approach. In: Santos, M.F., Machado, J., Novais, P., Cortez, P., Moreira, P.M. (eds) Progress in Artificial Intelligence. EPIA 2024. Lecture Notes in Computer Science(), vol 14968. Springer, Cham. https://doi.org/10.1007/978-3-031-73500-4_25
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