Accelerated eutrophication alters fish and aquatic health: a quantitative assessment by using integrative multimarker, hydrochemical, and GIS modelling method in an urban lake.

Abstract

The ramifications of anthropogenic activities on the environment and the welfare of aquatic life in lakes worldwide are becoming increasingly alarming. There is a lack of research in the Indian Himalayas on fish biomarker responses to stressful aquatic conditions and the use of environmetric modelling in GIS. Our research evaluates the environmental health of urban lakes in multiple basins using multi-biomarker endpoints (13 features) in Schizothorax niger and hydrochemical characterization (9 features) of water. The study covers 31 grids, each at a distance of 1 km2. This study demonstrated a statistically significant (P = 0.001) increase in white blood cells (WBC), mean cell size (MCH), helminth infection, and health assessment index score (HAIS) score in fish from a highly eutrophic cluster or basin compared to a reference cluster, which is indicative of environmental stress in fish. Based on hydrochemical similarities, the lake water datasets were divided into three categories using hierarchical cluster analysis (HCA). In the PCA analysis, the first three principal components were responsible for 78.1% of the data's variance. The first principal component (PC1) accounted for 57.4% of the variance and had a strong positive loading from ammonia, total phosphate, pH, nitrates, and total alkalinity for water quality parameters. Additionally, PC1 had a favourable loading from WBC, helminth infection (%), and the health assessment index score (HAIS) for biological endpoints. These findings are in alignment with the results of the multivariate analysis. The trophic state index (TSI) showed a significant (P < 0.05) increase in Cluster 1, which includes the peripheral areas of Hazratbal and Gagribal side (> 70), compared to the reference cluster. The multiple regression model indicates that ammonia, phosphate, and nitrate significantly impact the general health of fish (R2 > 0.7). A novel methodology for monitoring water quality fluctuations across different basins and clusters is presented in this study. By integrating fish health biomarkers and GIS technology, we have developed a comprehensive approach to evaluate the overall well-being of aquatic habitat. This technique may prove beneficial in the management of urban lentic water bodies in the Kashmir Himalayas and other comparable water systems around the globe, while also supporting sustainable practices.