Hybrid machine learning algorithms accurately predict marine ecological communities

Hybrid machine learning algorithms accurately predict marine ecological communities

Predicting ecological communities is highly challenging but necessary to establish effective conservation and monitoring programs. This study aims to predict the spatial distribution of nematode associations from 25 m to 2500 m water depth over an area of 350,000 km² and understand the major oceanog...

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Bibliographic Details
Main Authors: Luciana Erika Yaginuma, Fabiane Gallucci, Danilo Cândido Vieira, Paula Foltran Gheller, Simone Brito de Jesus, Thais Navajas Corbisier, Gustavo Fonseca
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Marine Science
Subjects:
nematodes
marine environment
artificial intelligence
supervised learning
unsupervised learning
baseline
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2025.1458014/full
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https://www.frontiersin.org/articles/10.3389/fmars.2025.1458014/full

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