Artificial Intelligence Analysis of Environmental DNA for Freshwater Fish Monitoring

Abstract

Introduction: Freshwater habitats contain fish communities that help maintain ecological balance, biodiversity, and sustainable use of the water resources. Nevertheless, various threats to the environment, including habitat destruction, pollution, climate change, and human activities, pose difficulties in efficient fish monitoring in freshwater habitats. Traditional fish monitoring techniques usually involve fish sampling and can be difficult to detect rare fish populations while disturbing aquatic creatures. Materials and Methods: In this study, an artificial intelligence-based environmental DNA (eDNA) technique for monitoring fish in freshwater habitats is presented. The suggested method uses DNA traces found in water for non-invasive identification of fish species and implements AI-based ecological analysis for biodiversity, species distribution, and habitat variation analysis. Results and Discussion: An integration of eDNA analysis and the use of artificial intelligence technology enhances biodiversity assessment of freshwaters by facilitating efficient fish community identification and changes in their ecology. Interpretation of complicated biological data through AI-aided analysis enables the establishment of the connection between the environment and the presence of fish communities. Such an approach eliminates the necessity of conducting resource-intensive surveys and provides useful information for further conservation and aquatic ecosystem management. Conclusion: AI-aided eDNA analysis is a promising way of implementing sustainable monitoring of fish communities in freshwater ecosystems.