Abstract
Inland waters are large contributors to global carbon dioxide (CO2) emissions, in part due to the vulnerability of dissolved organic matter (DOM) to microbial decomposition and respiration to CO2 during transport through aquatic systems. To assess the degree of this vulnerability, aquatic DOM is often incubated in standardized biolability assays. These assays isolate the dissolved fraction of aquatic OM by size filtration prior to incubation. We test whether this size selection has an impact on the bacterial community composition and the consequent dynamics of DOM degradation using three different filtration strategies: 0.2 μm (filtered and inoculated), 0.7 μm (generally the most common DOM filter size) and 106 μm (unfiltered). We found that bacterial community composition, based on 16S rRNA amplicon sequencing, was significantly affected by the different filter sizes. At the same time, the filtration strategy also affected the DOM degradation dynamics, including the δ13C signature. However, the dynamics of these two responses were decoupled, suggesting that filtration primarily influences biolability assays through bacterial abundance and the presence of their associated predators. By the end of the 41-day incubations all treatments tended to converge on a common total DOM biolability level, with the 0.7 μm filtered incubations reaching this point the quickest. These results suggest that assays used to assess the total biolability of aquatic DOM should last long enough to remove filtration artefacts in the microbial population. Filtration strategy should also be taken into account when comparing results across biolability assays.
| Original language | English |
|---|---|
| Pages (from-to) | 7141-7154 |
| Number of pages | 14 |
| Journal | Biogeosciences |
| Volume | 15 |
| Issue number | 23 |
| DOIs | |
| Publication status | Published - 30 Nov 2018 |
Funding
Acknowledgements. This work was carried out under the programme of the Netherlands Earth System Science Centre (NESSC), financially supported by the Ministry of Education, Culture and Science (OCW) (grant number 024.002.001). We thank the Systems Bioinformatics group at VU Amsterdam for the use of their flow cytometry equipment. We also thank the editor, Gerhard Herndl, and two anonymous referees for their comments and discussion which have improved this manuscript.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
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SDG 14 Life Below Water
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