Distinct Seasonal Patterns of Bacterioplankton Abundance and Dominance of Phyla α- Proteobacteria and Cyanobacteria in Qinhuangdao Coastal Waters Off the Bohai Sea

Abstract

Qinhuangdao coastal waters in northern China are heavily impacted by anthropogenic and natural activities, and we anticipate a direct influence of the impact on the bacterioplankton abundance and diversity inhabiting the adjacent coastal areas. To ascertain the anthropogenic influences, we first evaluated the seasonal abundance patterns and diversity of bacterioplankton in the coastal areas with varied levels of natural and anthropogenic activities and then analyzed the environmental factors which influenced the abundance patterns. Results indicated distinct patterns in bacterioplankton abundance across the warm and cold seasons in all stations. Total bacterial abundance in the stations ranged from 8.67 × 10⁴ to 2.08 × 10⁶ cells/mL and had significant (p < 0.01) positive correlation with total phosphorus (TP), which indicated TP as the key monitoring parameter for anthropogenic impact on nutrients cycling. Proteobacteria and Cyanobacteria were the most abundant phyla in the Qinhuangdao coastal waters. Redundancy analysis revealed significant (p < 0.01) influence of temperature, dissolved oxygen and chlorophyll a on the spatiotemporal abundance pattern of α-Proteobacteria and Cyanobacteria groups. Among the 19 identified bacterioplankton subgroups, α-Proteobacteria (phylum Proteobacteria) was the dominant one followed by Family II (phylum Cyanobacteria), representing 19.1-55.2% and 2.3-54.2% of total sequences, respectively. An inverse relationship (r = -0.82) was observed between the two dominant subgroups, α-Proteobacteria and Family II. A wide range of inverse Simpson index (10.2 to 105) revealed spatial heterogeneity of bacterioplankton diversity likely resulting from the varied anthropogenic and natural influences. Overall, our results suggested that seasonal variations impose substantial influence on shaping bacterioplankton abundance patterns. In addition, the predominance of only a few cosmopolitan species in the Qinhuangdao coastal wasters was probably an indication of their competitive advantage over other bacterioplankton groups in the degradation of anthropogenic inputs. The results provided an evidence of their ecological significance in coastal waters impacted by seasonal inputs of the natural and anthropogenic matter. In conclusion, the findings anticipate future development of effective indicators of coastal health monitoring and subsequent management strategies to control the anthropogenic inputs in the Qinhuangdao coastal waters.

Keywords: anthropogenic impacts; bacterioplankton abundance; environmental variables; phylogenetic diversity; redundancy analysis; seasonal variations.

FIGURE 1

Map of sampling stations.

FIGURE 2

Biplot of the principal component analysis (PCA) for environmental parameters in the sampling stations near Qinhuangdao coastal area. The two principal components (PC1 and PC2) explained 59.64% of total variation in environmental data, and shows clear partitioning of July and October samples from December and March along the PC1, and partitioning of July from October along PC2. PC1 and PC2 strongly correlated to variables NH₄-N and NO₃-N, and total nitrogen (TN), temperature (T) and Chlorophyll-a (Chl a), respectively. Total phosphate (TP), NO₂-N, and salinity were not correlated to PC1 and PC2. Blue arrows represent environmental parameters, and circles in color represents sampling points.

FIGURE 3

Fluorescence microscopy based quantification of total bacteria at the near-shore and off-shore stations near the Qinhuangdao coastal area of Bohai Sea. ‘W1’ to ‘W6’ indicate the different sampling stations.

FIGURE 4

Significant (p < 0.01) correlation between total bacterial abundance and total phosphorous. Values on Y-axis are shown in log-scale.

FIGURE 5

16S rRNA gene abundance (qPCR quantification) of major phylogenetic groups from coastal bacterioplankton assemblages in 6 stations near Qinhuangdao coastal area. The symbols and lines in black, red, green, blue, cyan, and magenta represent stations W1, W2, W3, W4, W5, and W6. Values on Y-axis are plotted in log-scale.

FIGURE 6

Biplot of redundancy analysis (RDA) showing relationship between the environmental variables and 16S rRNA gene abundance (qPCR quantification) of major phylogenetic groups in six stations near Qinhuangdao coastal area. The two RDA axes (RDA1 and RDA2) explained 70.35% of total variation in abundance data, and the significant (p < 0.01) explanatory variables were temperature (temp), dissolved oxygen (DO), and Chlorophyll a (Chl_a). Blue arrows represent different phylotypes, gray arrows represent environmental parameters, stars represent near-shore samples and circles represent off-shore samples. Different colors of the star or circle symbols represent different sampling time, with March samples in green, July samples in red, October samples in yellow and December samples in purple.

FIGURE 7

Composition and distribution of bacterioplankton assemblages at the 6 stations near Qinhuangdao coastal area. Percentage distribution of the 16S rRNA gene sequences at the (A) phylum level and (B) class level indicates higher relative abundance of subgroups Proteobacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria.