Using dissolved and particulate carbon for the prediction

Author(s):  
J.V. Prochnow ◽  
V. Spork ◽  
J. Jahnke ◽  
C. Schweim
Keyword(s):  
2016 ◽  
Vol 19 ◽  
pp. 77-85 ◽  
Author(s):  
Karl.A. Safi ◽  
Jason.B.K. Park ◽  
Rupert.J. Craggs

2020 ◽  
Author(s):  
Hualong Wang ◽  
Feng Chen ◽  
Chuanlun Zhang ◽  
Min Wang ◽  
Jinjun Kan

Abstract Background: Annually reoccurring microbial populations with strong spatial and temporal variations have been identified in estuarine environments, especially in those with long residence time such as the Chesapeake Bay (CB). However, it is unclear how microbial taxa interact with each other (e.g., mutualistic and competitive interactions) and how these interactions respond to their surrounding environments. Specifically, there is a lack of understanding of how these interactions influence microbiome population dynamics, and its adaptability and resilience to estuarine gradients. Results: Here, we constructed co-occurrence networks on prokaryotic microbial communities in the Bay, which included seasonal samples from seven spatial stations along the salinity gradients for three consecutive years. Our results showed that spatiotemporal variations of planktonic microbiomes promoted differentiations of the characteristics and stability of prokaryotic microbial networks in the CB estuary. Prokaryotic microbial networks are more stable seasonally than spatially, and microbes were more strongly connected during warm season compared to the associations during cold season. In addition, microbial interactions were more stable in the lower Bay (ocean side) than those in the upper Bay (freshwater side). Interestingly, compared to the abundant groups, the rare taxa such as SAR116 clade, SAR11 clade III, and OM182 clade contributed greatly to the stability and resilience of prokaryotic microbial interactions in the Bay. Modularity and cluster structures of microbial networks varied spatiotemporally, which provided valuable insights into the ‘small world’ (a group of more interconnected species), network stability, and habitat partitioning/preferences. Multivariate regression tree (MRT) analysis and Piecewise structural equation modeling (SEM) indicated that temperature, salinity and total suspended substances directly or indirectly (through nutrient availability, particulate carbon and Chl a) affected the distribution and associations of microbial groups, such as Actinobacteria, Bacteroidetes, Cyanobacteria, Planctomycetes, Proteobacteria, and Verrucomicrobia.Conclusion: Our results shed light on how spatiotemporal variations alter the nature and stability of prokaryotic microbial networks in the estuarine ecosystem, as well as the ability of planktonic microbiomes and their interactions to resist future disturbances.


1967 ◽  
Vol 24 (5) ◽  
pp. 909-915 ◽  
Author(s):  
R. W. Sheldon ◽  
T. R. Parsons

The size spectrum of particulate material in seawater can easily be expressed as total particle volume versus the logarithm of particle diameter. This appears to be the most informative way to present the data and it is also aptly suited to the classical divisions of nanno-, micro-, and macroplankton.A realistic measure of the volume of irregularly shaped particles such as phytoplankton chains could be made with a Coulter Counter. Particle volume measurements were in good agreement with estimates based on microscopic determination of particle diameter. There were also highly significant correlations between total particle volume, as indicated by the counter, and particulate carbon and nitrogen.


2019 ◽  
Vol 116 (46) ◽  
pp. 23309-23316 ◽  
Author(s):  
Ali Ebrahimi ◽  
Julia Schwartzman ◽  
Otto X. Cordero

The recycling of particulate organic matter (POM) by microbes is a key part of the global carbon cycle. This process is mediated by the extracellular hydrolysis of polysaccharides, which can trigger social behaviors in bacteria resulting from the production of public goods. Despite the potential importance of public good-mediated interactions, their relevance in the environment remains unclear. In this study, we developed a computational and experimental model system to address this challenge and studied how the POM depolymerization rate and its uptake efficiency (2 main ecosystem function parameters) depended on social interactions and spatial self-organization on particle surfaces. We found an emergent trade-off between rate and efficiency resulting from the competition between oligosaccharide diffusion and cellular uptake, with low rate and high efficiency being achieved through cell-to-cell cooperation between degraders. Bacteria cooperated by aggregating in cell clusters of ∼10 to 20 µm, in which cells were able to share public goods. This phenomenon, which was independent of any explicit group-level regulation, led to the emergence of critical cell concentrations below which degradation did not occur, despite all resources being available in excess. In contrast, when particles were labile and turnover rates were high, aggregation promoted competition and decreased the efficiency of carbon use. Our study shows how social interactions and cell aggregation determine the rate and efficiency of particulate carbon turnover in environmentally relevant scenarios.


Chemosphere ◽  
2020 ◽  
Vol 247 ◽  
pp. 125843
Author(s):  
Fangping Yan ◽  
Pengling Wang ◽  
Shichang Kang ◽  
Pengfei Chen ◽  
Zhaofu Hu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document