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Hybrid Intelligence for Marine Biodiversity: Integrating Citizen Science with AI for Enhanced Intertidal Conservation Efforts at Cape Santiago, Taiwan

Author

Listed:
  • Vincent Y. Chen

    (Institute of Fisheries Science, College of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106216, Taiwan)

  • Day-Jye Lu

    (School of Forestry & Resource Conservation, National Taiwan University, Taipei 106319, Taiwan)

  • Yu-San Han

    (Institute of Fisheries Science, College of Life Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106216, Taiwan)

Abstract

Marine biodiversity underpins the formation of marine protected areas (MPAs), necessitating detailed surveys to account for the dynamic temporal and spatial distribution of species influenced by tidal patterns and microhabitats. The reef rock intertidal zones adjacent to urban centers, such as Taiwan’s Cape Santiago, exhibit significant biodiversity, yet they are increasingly threatened by tourism-related activities. This study introduces an artificial intelligence (AI)-empowered citizen science (CS) approach within the local community to address these challenges. By integrating CS with AI, we establish a hybrid intelligence (HI) system that conducts in situ biological surveys and educational programs focused on reef ecological conservation. This initiative not only facilitates the collective gathering and AI-assisted analysis of critical data but also uses machine-learning outputs to gauge data quality, thus informing subsequent data collection and refinement strategies. The resulting collectivity and iterative enhancement foster a mutual and continuous HI learning environment. Our HI model proves instrumental in fostering community engagement and public involvement in CS endeavors, cultivating the skills necessary for documenting rocky intertidal biodiversity shifts. These efforts are pivotal for informing the design and governance of future MPAs, ensuring their efficacy and sustainability in marine conservation.

Suggested Citation

  • Vincent Y. Chen & Day-Jye Lu & Yu-San Han, 2024. "Hybrid Intelligence for Marine Biodiversity: Integrating Citizen Science with AI for Enhanced Intertidal Conservation Efforts at Cape Santiago, Taiwan," Sustainability, MDPI, vol. 16(1), pages 1-20, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:454-:d:1313168
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    References listed on IDEAS

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    1. Jarvis, Rebecca M. & Bollard Breen, Barbara & Krägeloh, Christian U. & Billington, D. Rex, 2015. "Citizen science and the power of public participation in marine spatial planning," Marine Policy, Elsevier, vol. 57(C), pages 21-26.
    2. Xiaoming Yang & Shamsulariffin Samsudin & Yuxuan Wang & Yubin Yuan & Tengku Fadilah Tengku Kamalden & Sam Shor Nahar bin Yaakob, 2023. "Application of Target Detection Method Based on Convolutional Neural Network in Sustainable Outdoor Education," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    3. Barbara Neumann & Athanasios T Vafeidis & Juliane Zimmermann & Robert J Nicholls, 2015. "Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding - A Global Assessment," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-34, March.
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