Environ Sci Pollut Res Int. 2025 Nov 23. doi: 10.1007/s11356-025-37240-3. Online ahead of print.
ABSTRACT
Diatom-based monitoring offers a cost-effective and reliable tool for assessing water quality in developing countries. As natural bio-indicators, diatoms respond sensitively to environmental changes, making them ideal for long-term ecological monitoring. The current paper aims to examine the potential use of a diatom-based tool at the genus level (generic diatom index (GDI)), when flora at the species level is poorly known, for water quality assessment in the Cambodian river systems. Nineteen monitoring sites within the Sangker River catchment have been chosen for the study, while eleven physicochemical parameters and trophic diatom index (TDI) values have been used to predict the response of GDI values. Basic statistical tests and linear regression (LM) were used to describe the spatio-temporal variation of water quality based on GDI classification. A total of 78 diatom genera were recorded, dominated by biraphid taxa (67%), and 13 genera accounted for ~ 90% of total abundance. GDI classification indicated that 10% of sites were of good quality, 53% moderate, and 37% poor, with water quality declining downstream and in areas influenced by urban and agricultural activities. The linear model revealed that GDI was significantly associated with nutrient- and oxygen-related parameters (orthophosphate, dissolved oxygen, and chloride) and correlated strongly with TDI (adjusted R2 = 0.96). Seasonal variation was also significant, highlighting the importance of temporal dynamics in tropical rivers. The current findings provided clear evidence of potential uses of diatom indices to assess the water quality in the Sangker River and other Cambodian river networks even at the genus level of determination. More importantly, diatom indices could be potential tools for long-term biomonitoring in developing countries like Cambodia, where the data and resources are limited. Consequently, the study suggested further investigation on the ecological sensitivity of diatom flora to localize their values, improving GDI classification performance within the tropical environment.
PMID:41275459 | DOI:10.1007/s11356-025-37240-3
