Artificial Intelligence Assessment of Mangrove Nursery Quality for Juvenile Fish

Abstract

Mangrove ecosystems are some of the highly productive ecosystems where they offer nursery habitats to juveniles for protection, food, and early development. The quality of the nursery habitats provided by mangrove ecosystems depends on environmental factors like vegetation structure, water quality, salinity range, oxygen content, sediments, and nutrients. Disturbances, degradation, and changes in the environment have affected the ability of mangrove ecosystems to nurture fish juveniles. In this research work, there is presented an artificial intelligence-based ecological assessment of mangrove nursery quality using environmental indicators. The evaluation is designed to study the relationships between mangrove properties and fish nursery conditions, and not the computation itself. Artificial intelligence methods were used for the evaluation in order to detect ecological trends in multiple habitat parameters and classify the nurseries depending on their quality levels. It was found out that good conditions of the mangrove ecosystem, including dense vegetation structure, stable water environment, and high productivity, create a favorable environment for juvenile fish growth. The evaluation has shown that artificial intelligence could be effectively used for ecological evaluations in terms of the identification of critical environmental factors affecting the nursery habitat quality