The underlying mechanisms of microbial community assembly in connective coastal environments are unclear. The coastal water area of northern Zhejiang, East China Sea, is a complex marine ecosystem with multiple environmental gradients, where the distributions and determinants of bacterioplankton communities remain unclear. We collected surface water samples from 95 sites across eight zones in this area for investigating bacterial community with 16S rRNA gene high-throughput sequencing. Bacterial alphadiversity exhibits strong associations with water chemical parameters and latitude, with 75.5% of variation explained by suspended particle. The composition of dominant phyla can group the sampling sites into four bacterial provinces, and most key discriminant phyla and families/genera of each province strongly associate with specific environmental features, suggesting that local environmental conditions shape the biogeographic provincialism of bacterial taxa. At a broader and finer phylogenetic scale, bacterial beta-diversity is dominantly explained by the shared variation of environmental and spatial factors (63.3%); meanwhile, the environmental determinants of bacterial β-diversity generally exhibit spatially structured patterns, suggesting that bacterial assembly in surface water is highly controlled by spatially structured environmental gradients in this area. This study provides evidence for the unique biogeographic pattern of bacterioplankton communities at an entire scale of this marine ecosystem.
The spatial distribution of microbial communities has recently been reliably documented in the form of a distance-similarity decay relationship. In contrast, temporal scaling, the pattern defined by the microbial similarity-time relationships (STRs), has received far less attention. As a result, it is unclear whether the spatial and temporal variations of microbial communities share a similar power law. In this study, we applied the 454 pyrosequencing technique to investigate temporal scaling in patterns of bacterioplankton community dynamics during the process of shrimp culture. Our results showed that the similarities decreased significantly (P = 0.002) with time during the period over which the bacterioplankton community was monitored, with a scaling exponent of w = 0.400. However, the diversities did not change dramatically. The community dynamics followed a gradual process of succession relative to the parent communities, with greater similarities between samples from consecutive sampling points. In particular, the variations of the bacterial communities from different ponds shared similar successional trajectories, suggesting that bacterial temporal dynamics are predictable to a certain extent. Changes in bacterial community structure were significantly correlated with the combination of Chl a, TN, PO4 (3-), and the C/N ratio. In this study, we identified predictable patterns in the temporal dynamics of bacterioplankton community structure, demonstrating that the STR of the bacterial community mirrors the spatial distance-similarity decay model.
Patterns of microbial distribution represent the integrated effects of historical and biological processes and are thus a central issue in ecology. However, there is still active debate on whether dispersal limitation contributes to microbial diversification in strongly connected systems. In this study, sediment samples were collected along a transect representing a variety of seawater pollution levels in the East China Sea. We investigated whether changes in sediment bacterial community structures would indicate the effects of the pollution gradient and of dispersal limitation. Our results showed consistent shifts in bacterial communities in response to pollution. More geographically distant sites had more dissimilar communities (r ؍ ؊0.886, P < 0.001) in this strongly connected sediment ecosystem. A variance analysis based on partitioning by principal coordinates of neighbor matrices (PCNM) showed that spatial distance (dispersal limitation) contributed more to bacterial community variation (8.2%) than any other factor, although the environmental factors explained more variance when combined (11.2%). In addition, potential indicator taxa (primarily affiliated with Deltaproteobacteria and Gammaproteobacteria) were identified; these taxa characterized the pollution gradient. This study provides direct evidence that dispersal limitation exists in a strongly connected marine sediment ecosystem and that candidate indicator taxa can be applied to evaluate coastal pollution levels.
The incidence of shrimp disease is closely associated with the microbial composition in surrounding water, but it remains uncertain whether microbial indicator phylotypes are predictive for shrimp health status (healthy or diseased). To test this idea, we combined the data from our previous works, to investigate the feasibility of indicator phylotypes as independent variables to predict the health status during a shrimp culture procedure. The results showed linearly increased dissimilarities (P<0.001) of the bacterioplankton community over time, while the communities dramatically deviated from this defined trend when disease occurred. This sudden shift in the bacterial community appears to cause severe mass mortality of the shrimps. In particular, we created a model to identify indicators that discriminated ponds with diseased shrimp populations from these with healthy shrimp populations. As a result, 13 indicative families were screened, in which seven are healthy indicator and six are diseased indictor. An improved logistic regression model additionally revealed that the occurrences of these indicator families could be predictive of the shrimp health status with a high degree of accuracy (>79 %). Overall, this study provides solid evidences that indicator phylotypes could be served as independent variables for predicting the incidences of shrimp disease.
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