Environmental DNA metabarcoding reveals the effect of environmental selection on phytoplankton community structure along a subtropical river

Abstract

The Dongjiang River, a major tributary of the Pearl River system that supplies water to more than 40 million people in Guangdong Province and neighboring regions of China, harbors rich biodiversity, including many endemic and endangered species. However, human activities such as urbanization, agriculture, and industrialization have posed serious threats to its water quality and biodiversity. To assess the status and drivers of phytoplankton diversity, which is a key indicator of aquatic ecosystem health, this study used Environmental DNA (eDNA) metabarcoding combined with machine learning methods to explore spatial variations in the composition and structure of phytoplankton communities along the Dongjiang River, including its estuary. The results showed that phytoplankton diversity exhibited spatial distribution patterns, with higher community structure similarity and lower network complexity in the upstream than in the downstream regions. Environmental selection was the main mechanism shaping phytoplankton community composition, with natural factors driving the dominance of Pyrrophyta, Ochrophyta, and Cryptophyta in the upstream regions and estuaries. In contrast, the downstream regions was influenced by high concentrations of pollutants, resulting in increased abundance of Cryptophyta. The random forest model identified temperature, dissolved oxygen, chlorophyll a, NO2−, and NH4+ as the main factors influencing the primary phytoplankton communities and could be used to predict changes during wet periods. This study provides valuable insights into the factors influencing phytoplankton diversity and community composition in the Dongjiang River, and demonstrates the application value of eDNA metabarcoding technique in large-scale, long-distance river biodiversity monitoring.