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PreprintCC BY-NC-ND 4.0EcoEvoRxiv

Large Language Models for Marine Protected Area Design and Management Planning

  • Ysobel Sims
  • Joseph M Maina
  • Arthur Tuda
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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.

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Cite

BibTeXRIS
BibTeX
@misc{sims2026large,
  title = {{Large Language Models for Marine Protected Area Design and Management Planning}},
  author = {Ysobel Sims and Joseph M Maina and Arthur Tuda},
  howpublished = {EcoEvoRxiv},
  year = {2026},
  month = oct,
  doi = {10.32942/x2rt2g},
  url = {https://ecoevorxiv.org/repository/view/15469/},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - UNPB
TI  - Large Language Models for Marine Protected Area Design and Management Planning
AU  - Ysobel Sims
AU  - Joseph M Maina
AU  - Arthur Tuda
PY  - 2026
DA  - 2026/10/12
PB  - EcoEvoRxiv
DO  - 10.32942/x2rt2g
UR  - https://ecoevorxiv.org/repository/view/15469/
AB  - 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.
ER  -