Application of Artificial Intelligence in Monitoring and Conservation of Freshwater Fish Diversity: A Review with Reference to Jayakwadi Dam (Nathsagar Reservoir), Maharashtra

Abstract

Freshwater reservoirs are ecologically important inland aquatic ecosystems that support high biodiversity and sustain inland fisheries. Artificial Intelligence (AI) has recently emerged as a powerful tool for ecological monitoring and fisheries management. The present review integrates conventional ichthyofaunal studies with modern AI-based approaches for monitoring freshwater fish diversity in the backwaters of Jayakwadi Dam (Nathsagar Reservoir) near Kaigaon Toka, Maharashtra. The reservoir, formed by impoundment of the Godavari River, supports diverse habitats including open waters, vegetated littoral zones, and shallow backwaters that sustain rich fish assemblages. Published studies indicate the occurrence of approximately 50–65 freshwater fish species belonging to major taxonomic orders such as Cypriniformes, Siluriformes, Osteoglossiformes, and Anabantiformes. AI techniques including machine learning-based species identification, remote sensing analysis, and predictive habitat modelling significantly enhance biodiversity monitoring and conservation planning. Integration of classical fish taxonomy with AI-driven ecological analytics provides a modern framework for invasive species detection and sustainable fisheries management.