Spatiotemporal patterns and environmental drivers of total and active bacterial abundances in Lake Taihu, China. (July 2020)

• Record Type: Journal Article
• Authors: Xie, Guijuan; Tang, Xiangming; Shao, Keqiang; Hu, Yang; Liu, Hao; Martin, Robbie M.; Gao, Guang
• Is Part Of: Ecological indicators. Volume 114(2020)
• Publication Date: 2020-07
• Subjects: Total bacteria -- Active bacteria -- Generalized additive models -- CTC -- Lake Taihu -- Eutrophic; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2020.106335
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: 120 samples were seasonally sampled to identify bacterial patterns in Lake Taihu. Total and active bacterial abundances (TB-AB) varied dramatically among seasons. On average, active bacteria accounted for ~10% of the total bacterial abundance. Nitrogen, phosphorus, organic carbon and temperature mostly shaped AB variation. AB is a more sensitive bioindicator of environmental changes than total bacteria. Abstract: Bacteria are a key component in lake ecosystems, playing a crucial role in driving biogeochemical and energy fluxes. In lake biomonitoring, false alarms have often been triggered due to the presence of abundant dead or dormant bacterial cells. Thus, quantification of the metabolically active and dormant cells is required for effective biomonitoring. In this study, 120 sites were seasonally sampled in a large, shallow, eutrophic lake (Taihu, China) to quantify the total bacterial (TB) and active bacterial (AB) abundances and explore their spatiotemporal distribution. Generalized additive models (GAMs) were used to identify the major environmental drivers of TB and AB dynamics. TB ranged from 7.57 × 10 4 to 1.84 × 10 8 cells mL −1, while AB ranged from 4.42 × 10 3 to 5.56 × 10 6 cells mL −1 . The proportion of AB was significantly higher in May (mean: 18.7%; cyanobacterial bloom thriving season) than in January or September (6.8% and 4.7%, respectively). GAMs indicated that dissolved oxygen, total dissolved nitrogen (TDN), total dissolved phosphorus and turbidity explained 47.8% of the TB variation, while TDN, dissolved organic carbon, water temperature and total phosphorus explained 72.7% of the AB variation. Our study showed that nutrients and physical factors are the major drivers of the TB and AB abundance variations in Lake Taihu. Bacterial responses to environmental variation were mostly non-linear. The high proportion of AB variation (72.7%) explained by environmental parameters indicates that active bacteria are more sensitive to environmental changes and could be more effective bioindicators for long-term monitoring in shallow eutrophic lakes.