Seasonality in Spatial Turnover of Bacterioplankton Along an Ecological Gradient in the East China Sea: Biogeographic Patterns, Processes and Drivers

Abstract

Seasonal succession in bacterioplankton is a common process in marine waters. However, seasonality in their spatial turnover is largely unknown. Here, we investigated spatial turnover of surface bacterioplankton along a nearshore-to-offshore gradient in the East China Sea across four seasons. Although seasonality overwhelmed spatial variability of bacterioplankton composition, we found significant spatial turnover of bacterioplankton along the gradient as well as overall seasonal consistency in biogeographic patterns (including distance–decay relationship and covariation of community composition with distance to shore) with subtle changes. Bacterioplankton assembly was consistently dominated by deterministic mechanisms across seasons, with changes in specific processes. We found overall seasonal consistency in abiotic factors (mainly salinity and nitrogen and phosphorus nutrients) shaping bacterioplankton composition, while phytoplankton showed a similar influence as abiotic factors only in spring. Although key taxa responsible for bacterioplankton spatial turnover showed certain season-specificity, seasonal switching between closely related taxa occurred within most dominant families. Moreover, many close relatives showed different responding patterns to the environmental gradients in different seasons, suggesting their differences in both seasonally climatic and spatially environmental preferences. Our results provide insights into seasonal consistency and variability in spatial turnover of bacterioplankton in terms of biogeographic patterns, ecological processes, and external and internal drivers.

Sargasso Sea bacterioplankton community structure and drivers of variance as revealed by DNA metabarcoding analysis

“…Environmental selection, primarily temperature, was stronger than dispersal limitation in accounting for variation among bacterial assemblages (17% vs 11%); this finding agrees with several prior studies of marine bacterioplankton ( Hanson et al, 2012 ; Hu et al, 2020 ; Milici et al, 2016 ; Sunagawa et al, 2015 ). Relatively weaker spatial patterning in bacteria supports the “size-dispersal” hypothesis, i.e ., that smaller organisms have higher dispersal rates, especially when dispersal is primarily passive ( De Bie et al, 2012 ).…”

“…Our findings are in general accord with Mo et al (2018) who likewise found stochastic factors to be primary in bacterioplankton community assembly in open-ocean habitat, albeit at a somewhat lower level of dominance (57%). However, several other studies found deterministic factors to be more important relative to neutral processes in similar scenarios ( Allen et al, 2020 ; Hu et al, 2020 ; Vergin et al, 2017 ; Wu et al, 2018 ). Although spatial factors comprise a portion of the neutral process ( Hubbell, 2001 ), the strength of the NCM in our study does not contradict the relatively small spatial effect revealed by variation partitioning.…”

T4‐like myovirus community shaped by dispersal and deterministic processes in the South China Sea

“…Bray–Curtis similarity is one of the most commonly used similarity quantification methods when it comes to ecological abundance data collected at different sampling locations (Legendre and Legendre, 2012; Ricotta and Podani, 2017). Principal coordinates analysis explores similarities or dissimilarities, such as Bray–Cutis similarity, and takes species identity into account, which is a better method of analysing bacterial community structure data for VPA (Mohammadi and Prasanna, 2003; Legendre and Legendre, 2012; Hamdan et al ., 2013; Nagaraj et al ., 2017; Hu et al ., 2020). To avoid collinearity in the statistical calculation, principal coordinates axes with a cumulative 73.9% variation based on Bray–Curtis similarity were used to summarize the bacterial community structure (relative abundance data) for VPA.…”

Disentangling the abundance and structure of Vibrio communities in a semi-enclosed Bay with mariculture (Dongshan Bay, Southern China)

“…Mariculture represents one of the fastest growing industrial sectors in the world, but from the perspective of nutrient load and structural damage, the impact of mariculture on the environment is considerable. Microorganisms form the basis of marine food webs and are crucial for biogeochemical cycles [15] , [18] , [51] . Yet, there are many unknowns on how microorganisms respond to environmental interferences from mariculture activities [2] , [27] , [38] , [47] .…”

“…Microorganisms are regarded as one of the major food web components of coastal ecosystems controlling biogeochemical cycles in coastal environments to a large extent [51] . Thus, exploring the spatial pattern of microbial communities related to environmental factors is crucial to reveal the role of microbial communities for the entire coastal food web and biogeochemical cycles [15] , [18] , [40] .…”