# AquaX: An enhanced and revised AquaMaps framework to model marine species distributions and biodiversity

**Authors:** Gabriel Reygondeau, Yulia Egorova, Kristina Boerder, Derek P. Tittensor, Kristin Kaschner, Kathleen Kesner-Reyes, Nicolas Bailly, William W. L. Cheung, Athanassios Tsikliras, Athanassios Tsikliras, Athanassios Tsikliras

PMC · DOI: 10.1371/journal.pone.0335823 · PLOS One · 2026-02-20

## TL;DR

AquaX is an improved marine species distribution modeling tool that enhances accuracy and resolution for better conservation planning.

## Contribution

AquaX introduces a next-generation platform with ten machine learning algorithms and higher spatial resolution for marine species modeling.

## Key findings

- AquaX provides species range maps for numerous species with improved accuracy.
- The platform enables habitat suitability projections for present and future climate scenarios.
- AquaX integrates expert knowledge and updated data for refined species distribution modeling.

## Abstract

Marine biodiversity underpins ecosystem health and is critical for the provision of essential ecological services. Global efforts to mitigate biodiversity loss are underway but require comprehensive knowledge on the biogeography of species to be effective. However, key challenges limit comprehensive mapping of species distributions, including the ecosystem complexity and difficulty of sampling the marine realm. Global initiatives such as AquaMaps pioneered large-scale marine species mapping using species distribution models or ecological niche models and provided the knowledge base for effective marine conservation and management. Recently, methodological and data advances have enabled a more modern and robust approach that enables higher resolution outputs more suited to conservation applications at all scales. Building on AquaMaps, we developed a next-generation marine species habitat suitability modelling platform called AquaX, providing a suite of advances that include an ensemble of ten machine learning algorithms, enabling spatial uncertainty assessments, validation indices, and ecological niche representation at a ten-fold improved spatial resolution of 0.05°. Furthermore, AquaX integrates (i) accepted taxonomy from the World Register of Marine Species, (ii) species-specific ecological, physiological, and biogeographical information (D3-Ocean system), (iii) updated occurrence records validated through expert input, and (iv) refined species range maps using expert knowledge and biogeographical divisions. AquaX also projects species’ habitat suitability for both present and future conditions based on two time periods and three climate scenarios. This work provides species range maps for numerous species compared to previously available datasets and improves the accurate use of observational data. The approaches described here improve predictive accuracy at scales more relevant to marine biodiversity conservation and offer an openly accessible tool to support marine biodiversity research and conservation planning under accelerating environmental change. AquaX represents an important step forward in species distribution modeling, enabling researchers and policymakers to better understand marine biodiversity patterns and develop more effective conservation strategies.

## Full-text entities

- **Diseases:** ERM (MESH:C535477), WoRMS (MESH:D016773), PAs (MESH:D004832), ORCID iD (MESH:C535742)
- **Chemicals:** AquaX (-), carbon (MESH:D002244)
- **Species:** Hippocampus barbouri (Barbour's seahorse, species) [taxon 109276], Homo sapiens (human, species) [taxon 9606], Cynoscion arenarius (sand weakfish, species) [taxon 80640], Pterois volitans (red lionfish, species) [taxon 185886], Salmonidae (salmonids, family) [taxon 8015], Salmo trutta trutta (sea trout, subspecies) [taxon 227976], Chrysoblephus puniceus (red stumpnose, species) [taxon 655099], Thunnus obesus (bigeye tuna, species) [taxon 8241], Entelurus aequoreus (snake pipefish, species) [taxon 161455]
- **Mutations:** S10A, C) from 1995-2014-2081-2100

## Full text

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## Figures

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## References

99 references — full list in the complete paper: https://tomesphere.com/paper/PMC12923144/full.md

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Source: https://tomesphere.com/paper/PMC12923144