Determinism of bacterial metacommunity dynamics in the southern East China Sea varies depending on hydrography

Abstract

Spatial variation of communities composition (metacommunities) results from multiple assembly mechanisms, including environmental filtering and dispersal; however, whether and why the relative importance of the assembly mechanisms in shaping bacterial metacommunity changes through time in marine pelagic systems remains poorly studied. Here, we applied the elements of metacommunity structure framework and the variation partitioning framework to examine whether temporal variation of hydrographic conditions influences bacterioplankton metacommunity dynamics in the southern East China Sea (ECS). The spatiotemporal variation of bacterial communities composition was revealed using 454 pyrosequencing of 16S rDNA. In addition to the whole bacterial community, we analyzed four dominant taxonomic groups (Cyanobacteria, Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria) separately. Our analyses indicate that, considering the whole community level, the determinism of metacommunity structure varied among seasons. When the degree of connectivity was low (December), the metacommunity exhibited random distribution and was explained mainly by the environmental component. However, Clementsian metacommunity was found at intermediate connectivity (May), during which the environmental and spatial predictors were both significant. When connectivity was high (August), a random distribution pattern was found and no significant effect of environmental filtering or dispersal limitation was detected. Nevertheless, when considering different taxonomic groups, the differences in metacommunity dynamics among groups were found. Our results suggest that the driving forces of metacommunity dynamics varied depending on hydrography, as the degrees of environmental heterogeneity and connectivity among habitat patches were determined by circulation pattern. Moreover, mechanisms varied among different taxonomic groups, suggesting that differential dispersal capacity among taxonomic groups should be integrated into community assembly studies.

Local Environmental Conditions Shape Generalist But Not Specialist Components of Microbial Metacommunities in the Baltic Sea

“…Altogether, studies highlight that local environmental conditions structure the regional distribution of bacterioplankton populations into distinct metacommunities. Yet, temporal changes in assembly mechanisms have also been demonstrated for bacterial communities in rock pools (Langenheder et al, 2012) and in the southern East China Sea (Yeh et al, 2015), and accordingly, assembly mechanisms estimated over time in the current dataset indicated differences between months ( Figure 1 ), so that, for example, in April and August the total communities were structured according to both the NM and PDs while the May and September communities were structured by SS and ME. In conclusion, although the main assembly process was SS, there was at times a substantial effect of spatial factors in shaping community structure, indicating that dispersal-driven assembly processes were also important, and these results highlight seasonal variation in the assembly of microbial communities and indicate the need for studying temporal dynamics in greater detail to understand microbial metacommunity dynamics.…”

“…The neutral model (NM), in turn, emphasizes the importance of stochastic assembly processes (Logue et al, 2011). To our knowledge, three studies examining assembly mechanisms of bacterioplankton communities have been performed in marine environments; in the southern East China Sea, among Vibrio cholerae strains collected around the central California coast, and for 16 mainly coastal sites distributed globally (Keymer et al, 2009; Barberan and Casamayor, 2010; Yeh et al, 2015). In contrast, limnic environments are better understood (see, e.g., Beisner et al, 2006; Van der Gucht et al, 2007; Lindström et al, 2010; Logue and Lindström, 2010; Langenheder et al, 2012; Lindström and Langenheder, 2012; Adams et al, 2014).…”

“…Collectively, examination of assembly mechanisms of bacterioplankton communities in aquatic environments indicates that SS (i.e., local environmental conditions) is the main driver of bacterial community structure. Nevertheless, although local environmental conditions are the dominant factor in shaping bacterioplankton communities, both Langenheder et al (2012) and Yeh et al (2015) observed temporal changes in assembly processes. Thus, information is lacking on the factors affecting bacterioplankton assembly mechanisms, including the magnitude and prevalence of temporal changes, or the influence of different taxa-intrinsic characteristics such as dispersal capacity, or a generalist versus specialist nature (Lindström and Langenheder, 2012).…”

Evaluating community–environment relationships along fine to broad taxonomic resolutions reveals evolutionary forces underlying community assembly

“…In addition to the spatial variation, the prokaryotic communities might be also sensitive to the seasonal variation, and this temporal dynamics might be also well represented by broadly resolved data. In fact, the original studies of cases #7 and #8 have reported clear seasonal community dynamics using order-level or class-level compositions (Gilbert et al, 2009;Yeh et al, 2015).…”

“…Sequence-based prokaryotic community data sets We used eight data sets: (1) Lauber 'America-Soils' study (Lauber et al, 2009) (referred to as case #1 hereafter), (2) Chu 'Arctic-Soils' study (Chu et al, 2010) (referred to as case #2 hereafter), (3) Ramirez 'NYpark-Soils' study (Ramirez et al, 2014) (referred to as case #3 hereafter), (4) Zarraonaindia 'NYfarmSoils' study (Zarraonaindia et al, 2015) (referred to as case #4 hereafter), (5) Sunagawa 'TaraSur-Seawaters' study (Sunagawa et al, 2015) (referred to as case #5 hereafter), (6) Sunagawa 'TaraChl-Seawaters' study (Sunagawa et al, 2015) (referred to as case #6 hereafter), (7) Gilbert 'WEC-Seawaters' study (Gilbert et al, 2012) (referred to as case #7 hereafter) and (8) Yeh 'SECS-Seawaters' study (Yeh et al, 2015) (referred to as case #8 hereafter) to test our theoretical framework regarding how the strength of communityenvironment relationships varies with changes in taxonomic resolution (Figure 1). We summarize the characteristics of these sequence-based prokaryotic community data sets in Table 1.…”