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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 complexity of ocean ecosystems and the 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 develop 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.
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Reygondeau, Gabriel, et al. “AquaX: An Enhanced and Revised AquaMaps Framework to Model Marine Species Distributions and Biodiversity.” bioRxiv, 20 Oct. 2025, https://doi.org/10.1101/2025.10.19.683322v1.
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Join us on Thursday, March 26, 2026, for the University of Miami Smart Cities MIAMI Conference. This 10th edition celebrates a decade of innovation and progress in building smart cities as we envision the future. This event is a collaboration between the School of Architecture, College of Engineering, and the Frost Institute for Data Science and Computing. Read more “Smart Cities MIAMI 2026: 10 Years of Lessons, Leaps, and the Road Ahead 3/26” →
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The Institute congratulates Dr. Mingzhe Chen, one of only 119 in the field of Computer Science worldwide and one of 2,670 in the United States to make the Clarivate 2025 list of the World’s Highly Cited Researchers. Dr. Chen was one of three University of Miami professors honored.* Read more “Mingzhe Chen identified by Clarivate as a Highly Cited Researcher in 2025” →
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