Temporal patterns of phyto- and bacterioplankton and their relationships with environmental factors in Lake Taihu, China

Chemosphere. 2017 Oct:184:299-308. doi: 10.1016/j.chemosphere.2017.06.003. Epub 2017 Jun 2.

Abstract

Phytoplankton and bacterioplankton are integral components of aquatic food webs and play essential roles in the structure and function of freshwater ecosystems. However, little is known about how phyto- and bacterioplankton may respond synchronously to changing environmental conditions. Thus, we analyzed simultaneously the composition and structure of phyto- and bacterioplankton on a monthly basis over 12 months in cyanobacteria-dominated areas of Lake Taihu and compared their responses to changes in environmental factors. Metric multi-dimensional scaling (mMDS) revealed that the temporal variations of phyto- and bacterioplankton were significant. Time lag analysis (TLA) indicated that the temporal pattern of phytoplankton tended to exhibit convergent dynamics while bacterioplankton showed highly stable or stochastic variation. A significant directional change was found for bacterioplankton at the genus level and the slopes (rate of change) and regression R2 (low stochasticity or stability) were greater if Cyanobacteria were included, suggesting a higher level of instability in the bacterial community at lower taxonomy level. Consequently, phytoplankton responded more rapidly to the change in environmental conditions than bacterioplankton when analyzed at the phylum level, while bacterioplankton were more sensitive at the finer taxonomic resolution in Lake Taihu. Redundancy analysis (RDA) results showed that environmental variables collectively explained 51.0% variance of phytoplankton and 46.7% variance of bacterioplankton, suggesting that environmental conditions have a significant influence on the temporal variations of phyto- and bacterioplankton. Furthermore, variance partitioning indicated that the bacterial community structure was largely explained by water temperature and nitrogen, suggesting that these factors were the primary drivers shaping bacterioplankton.

Keywords: Bacterioplankton; Environmental factors; Phytoplankton; Time lag analysis.

MeSH terms

  • China
  • Cyanobacteria / physiology*
  • Ecosystem*
  • Lakes / microbiology
  • Nitrogen / analysis
  • Phytoplankton / physiology*
  • Temperature
  • Time Factors

Substances

  • Nitrogen