{
  "abstract": "Achieving biodiversity targets requires advances in marine conservation planning and action. We make three arguments about large language models (LLMs): they add more value when embedded within decision-support systems; they integrate fragmented expertise, data, and tools; they can increase capacity in under-resourced settings through co-design. We illustrate these arguments with a conceptual LLM-enabled marine protected area design and management framework, and address concerns about data, governance, and knowledge equity.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "Ysobel Sims"
    },
    {
      "name": "Joseph M Maina"
    },
    {
      "name": "Arthur Tuda"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cjpp1ec3gm39f.bib",
  "cited_by": 0,
  "doi": "10.32942/x2rt2g",
  "fulltext_url": null,
  "id": "cjpp1ec3gm39f",
  "issns": [],
  "landing_url": "https://ecoevorxiv.org/repository/view/15469/",
  "language": null,
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode",
  "metadata_licence": null,
  "native_subjects": [
    [
      "bepress",
      "Artificial Intelligence and Robotics"
    ],
    [
      "bepress",
      "Biodiversity"
    ],
    [
      "bepress",
      "Bioinformatics"
    ],
    [
      "bepress",
      "Natural Resources and Conservation"
    ],
    [
      "bepress",
      "conservation informatics"
    ],
    [
      "bepress",
      "global biodiversity framework"
    ],
    [
      "bepress",
      "life below water"
    ],
    [
      "bepress",
      "machine learning"
    ],
    [
      "bepress",
      "marine biodiversity"
    ],
    [
      "bepress",
      "marine conservation"
    ],
    [
      "openalex",
      "2308|Coastal and Marine Management"
    ]
  ],
  "openalex": "W7221527154",
  "pdf_url": "https://ecoevorxiv.org/repository/object/15469/download/26819/",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-12",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cjpp1ec3gm39f.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:37Z",
      "native_id": "15469",
      "source": "ecoevorxiv",
      "url": "https://ecoevorxiv.org/repository/view/15469/"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "bepress:Bioinformatics",
      "subfield": "bioinformatics"
    },
    {
      "field": "biology",
      "origin": "bepress:Natural Resources and Conservation",
      "subfield": "ecology"
    }
  ],
  "title": "Large Language Models for Marine Protected Area Design and Management Planning",
  "title_text": "Large Language Models for Marine Protected Area Design and Management Planning",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:37Z",
  "url": "https://research.draconitic.com/paper/cjpp1ec3gm39f",
  "venue": "EcoEvoRxiv",
  "versions": []
}