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Fisheries Depletion: The Factors and Actors Involved in the Transfer of Fish From Developing Countries to Developed Ones

Author

Listed:
  • Roberto Mielgo

    (Internacional Fisheries Consultant, The Kanikosen Project)

  • Miren Gutiérrez

    (University of Deusto)

  • Guillermo G. Almazor

    (DNSimple)

Abstract

This article examines how distant-water fishing by wealthy nations depletes fish stocks and harms food security in developing countries while benefiting richer markets. It explores the impact of practices like bycatch, the use of fish aggregating devices, and illegal fishing on the Global South. The findings show that industrial fleets from wealthier countries use sophisticated technology to exploit poorly regulated fisheries, outcompeting local fishers and causing economic and ecological damage. Fisheries data analysis and algorithmic tracking are not working for developing nations either. The research calls for stronger international cooperation, better fisheries management, and support for small-scale fishers to protect livelihoods and ensure sustainable fish stocks.

Suggested Citation

  • Roberto Mielgo & Miren Gutiérrez & Guillermo G. Almazor, 2024. "Fisheries Depletion: The Factors and Actors Involved in the Transfer of Fish From Developing Countries to Developed Ones," Development, Palgrave Macmillan;Society for International Deveopment, vol. 67(1), pages 75-84, June.
    • Handle: RePEc:pal:develp:v:67:y:2024:i:1:d:10.1057_s41301-024-00412-8
    DOI: 10.1057/s41301-024-00412-8
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    References listed on IDEAS

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    1. Davies, R.W.D. & Cripps, S.J. & Nickson, A. & Porter, G., 2009. "Defining and estimating global marine fisheries bycatch," Marine Policy, Elsevier, vol. 33(4), pages 661-672, July.
    2. Daniel Pauly & Dirk Zeller, 2016. "Catch reconstructions reveal that global marine fisheries catches are higher than reported and declining," Nature Communications, Nature, vol. 7(1), pages 1-9, April.
    3. Ilia Shumailov & Zakhar Shumaylov & Yiren Zhao & Nicolas Papernot & Ross Anderson & Yarin Gal, 2024. "AI models collapse when trained on recursively generated data," Nature, Nature, vol. 631(8022), pages 755-759, July.
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