Restructuring of Phytoplankton Functional Groups at the Ganga–Yamuna Confluence under Changing Environmental Variables at Prayagraj, India

Abstract

River confluences are dynamic ecological transition zones where contrasting physicochemical conditions can restructure phytoplankton communities. However, the functional organisation of phytoplankton at large tropical river confluences remains poorly understood. This study investigated the spatial and seasonal dynamics of phytoplankton functional groups (FGs) and their environmental drivers at the Ganga–Yamuna confluence (Triveni Sangam), Prayagraj, India. Monthly sampling was conducted at five sites from January to December 2025. Physicochemical parameters, chlorophyll-a and phytoplankton communities were analysed, and species were classified into functional groups following the Reynolds–Padisák system. Spatial and seasonal differences were evaluated using one-way ANOVA, PERMANOVA, SIMPER, non-metric multidimensional scaling (NMDS), and principal coordinates analysis (PCO), while redundancy analysis (RDA) identified the main environmental drivers. A total of 29 phytoplankton functional groups were recorded. FG A remained dominant throughout the study, with the highest contribution during winter (45.01%) and monsoon (39.52%). PERMANOVA showed that community composition differed significantly among seasons (P = 0.001) but not among river zones (P = 0.073), indicating that seasonal hydrology was the principal driver of functional-group assembly. Post-monsoon communities shifted towards turbulence-associated FG T and enrichment-related FG K, reflecting hydrological reorganisation after peak discharge. RDA identified electrical conductivity, total dissolved solids, pH, chlorophyll-a, dissolved oxygen, and temperature as the principal environmental drivers of functional-group composition. These findings suggest that the Ganga–Yamuna confluence functions as an ecological filter rather than a simple mixing zone and highlight the value of phytoplankton functional groups as sensitive indicators for monitoring and managing large tropical river ecosystems.