Ecosystem Health Assessment of Hulun Lake Using an
eDNA
Metabarcoding‐Based Phytoplankton Index of Biotic Integrity
Qi An, Ruiying Fu, Hao Cui, Yuan Wang, Yihan Huo, Yang Bai, Wei Ding, Bowen Xiao, Chengzhen Jia, Huamin Liu, Lixin Wang ABSTRACT
Hulun Lake, one of the largest freshwater lakes in China, is currently experiencing significant water quality deterioration. Therefore, water quality assessment is of paramount importance, as it not only provides critical insights into the current pollution status of lakes but also offers a scientific basis for effective lake management and ecological restoration. Using environmental DNA‐metabarcoding data from 13 sampling sites in Hulun Lake in June 2023, our study explored the spatial variation of α‐diversity, the community composition, and phytoplankton index of biotic integrity (P‐IBI). A total of 431 phytoplankton species were identified across 10 phyla, 191 families, and 335 genera, with Chlorophyta and Bacillariophyta predominating. Biodiversity was higher in the northern and southern regions, except for the site XHK, but lower in the central region. P‐IBI scores exhibited clear spatial variation, with relatively high scores in the central and northern regions, except for the site XHK, indicating comparatively favorable ecological conditions. In contrast, lower P‐IBI scores were observed in the southern region, except for DNHWZ and GZ, suggesting relatively greater ecological degradation. The P‐IBI scores were significantly negatively correlated with Water Quality Index (WQI) values, indicating that higher biotic integrity was generally associated with better physicochemical water quality. RDA and Spearman rank correlation analyses revealed that ammonia nitrogen (NH 3 –N) and total organic carbon (TOC) were positively correlated with P‐IBI, whereas temperature (T) and total nitrogen (TN) showed negative correlations with P‐IBI, indicating that spatial variation in P‐IBI was closely associated with nutrient status and organic carbon availability. Lake management should integrate both P‐IBI and WQI‐based assessment approaches, providing a scientifically robust basis for the identification of environmental pressures and the diagnosis of ecological health.