Source identification of phosphorus in the river-lake interconnected system using microbial community fingerprints

Abstract

Phosphorus, one of the primary limiting factors for eutrophication, plays a crucial role in the ecology health of aquatic ecosystems. However, understanding phosphorus bioavailability and source contributions in contaminated lake sediments which could help develop effective eutrophication management plans is limited largely due to the lack of appropriate methods in large catchments with a complex arrangement of sources. Based on the significant relationships between sediment, phosphorus and microbial community, source-specific microbial community fingerprints formed by machine-learning classification SourceTracker might shed light on determining dominant phosphorus sources in the river-lake systems in the era of high-throughput sequencing. This study was conducted in Dongting Lake that suffered accelerated eutrophication due to considerable phosphorus input from the inflow-rivers. The results of phosphorus fractionation according to the Standards, Measurements and Testing harmonized procedure indicated that sediments in the central lake had a higher concentration of non-apatite inorganic phosphorus (Mann-Whitney U test), which deserves greater attention on the risk of phosphorus release. The significant relationships between phosphorus fractionations, sediment and bacterial community were established with the spearman correlation and network analysis. SourceTracker analysis indicated that the major inflow-rivers of phosphorus sources to Dongting Lake were the Songzi, Miluo, and Xinqiang Rivers. The effects of sediment diffusion distance on phosphorus source apportionment were further confirmed. Taken together, our results contribute to an improved understanding of phosphorus fractionations and source contributions in the river-lake systems and its potential impact to eutrophication management plans.