Towards a physiological response of fishes under variable environmental conditions: An approach through neural network

Present study aims to explore the effectiveness of environmental factors as predictive markers for assessing their impact on stress and endocrine physiology in selected five ecologically important fish species of Sundarban mangrove estuarine area, India. Our goal was to develop a realistic integrated conceptual model to analyze and envisage the consequence of fluctuating environmental parameters on the stress physiology of these fishes and their adaptive responses to thrive in such environment. Fishes were collected monthly throughout the year from 3 different study sites and various anti-oxidant (enzymatic and non-enzymatic) and detoxification enzymes were measured. Levels of the stress hormone cortisol and reproductive hormone 17β-estradiol were also measured as indicators of stress accumulation and reproductive status of the selected fish species. The study sites showed variations in physical factors such as pH, dissolved oxygen, temperature and salinity, which may be related to environmental fluctuation and/or pollution level. Such panel of multiple enzyme and hormone biomarkers in fish might be a useful tool to develop an assessment model. This study demonstrated a sharp indication of variation in the antioxidant enzyme profiles depending on the physical environment but the changes is exclusively site as well as species specific. To justify our assumptions cluster and non-metric multidimensional scaling (NMDS) analysis have been done to investigate the ordination of physiological parameters and water quality parameters; if it varies for each species or not. Levels of superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), glutathione peroxidise (GPx), malondialdehyde (MDA) and glutathione (GSH) showed variations depending on the physical environment but the changes is exclusively site as well as species specific. Finally, the prediction model and NMDS scaling confirmed MDA, GST and GSH as decisive factor to envisage steroid hormone, whereas organic carbon, temperature, ammonia and alkalinity as the major contributor of its prediction.