Seasonal and Spatiotemporal Dynamics of Plankton Communities Using eDNA Metabarcoding in Singal Reservoir

Area of Science:

• Ecology
• Environmental Science
• Molecular Biology

Background:

• Understanding plankton community assembly is crucial for predicting ecosystem responses to environmental change in reservoirs.
• Environmental DNA (eDNA) metabarcoding offers a powerful tool for assessing aquatic biodiversity.
• Reservoir ecosystems face unique challenges due to fluctuating environmental conditions.

Purpose of the Study:

• To investigate the influence of environmental drivers (temperature, dissolved oxygen, spatial gradients) on plankton community structure in Singal Reservoir.
• To analyze seasonal and spatial variations in phytoplankton and zooplankton communities using eDNA metabarcoding.
• To identify specific environmental preferences of key plankton taxa.

Main Methods:

• Environmental DNA (eDNA) metabarcoding targeting the V9 region of 18S rRNA was employed.
• Water samples were collected across seasonal (spring, autumn) and spatial (inflow, middle, outflow, depth) scales.
• Statistical analyses, including PERMANOVA and Spearman correlations, were used to link community structure with environmental variables.

Main Results:

• Environmental factors explained over 38% of both phytoplankton and zooplankton community variation, with total nitrogen being a significant driver for phytoplankton.
• Phytoplankton and zooplankton communities exhibited distinct seasonal patterns, with higher species richness in autumn.
• Temperature and dissolved oxygen gradients created specific niches, influencing the distribution of diatoms and dinoflagellates, while spatial location was more influential than depth for zooplankton.

Conclusions:

• Environmental selection, particularly temperature and dissolved oxygen, are primary drivers of plankton community structure in reservoir ecosystems.
• The findings highlight the importance of considering environmental gradients in predicting plankton dynamics under climate change.
• This research provides valuable insights for reservoir management and conservation strategies.