Publications by authors named "Agnes Duhamet"
Article Synopsis
- The study highlights that there is a lack of data on marine fish species' extinction risks, which hampers effective conservation planning, particularly for teleost fishes.
- By using machine learning algorithms, researchers predicted an increased IUCN extinction risk for marine fishes from 2.5% to 12.7%, identifying specific traits like small geographic range and low growth rate as indicators of threat.
- The research proposes integrating these predictions into conservation strategies, emphasizing the importance of prioritizing marine protected areas, especially in less diverse regions that are still crucial for vulnerable species.
The bathymetric and geographical distribution of marine species represent a key information in biodiversity conservation. Yet, deep-sea ecosystems are among the least explored on Earth and are increasingly impacted by human activities. Environmental DNA (eDNA) metabarcoding has emerged as a promising method to study fish biodiversity but applications to the deep-sea are still scarce.
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