Effect of CO <sub>2</sub> enrichment on bacterial metabolism in an Arctic fjord
Bibliographic record
Abstract
Abstract. The anthropogenic increase of carbon dioxide (CO2) alters the seawater carbonate chemistry, with a decline of pH and an increase in the partial pressure of CO2 (pCO2). Although bacteria play a major role in carbon cycling, little is known about the impact of rising pCO2 on bacterial carbon metabolism, especially for natural bacterial communities. In this study, we investigated the effect of rising pCO2 on bacterial production (BP), bacterial respiration (BR) and bacterial carbon metabolism during a mesocosm experiment performed in Kongsfjorden (Svalbard) in 2010. Nine mesocosms with pCO2 levels ranging from ca. 180 to 1400 μatm were deployed in the fjord and monitored for 30 days. Generally BP gradually decreased in all mesocosms in an initial phase, showed a large (3.6-fold average) but temporary increase on day 10, and increased slightly after inorganic nutrient addition. Over the wide range of pCO2 investigated, the patterns in BP and growth rate of bulk and free-living communities were generally similar over time. However, BP of the bulk community significantly decreased with increasing pCO2 after nutrient addition (day 14). In addition, increasing pCO2 enhanced the leucine to thymidine (Leu : TdR) ratio at the end of experiment, suggesting that pCO2 may alter the growth balance of bacteria. Stepwise multiple regression analysis suggests that multiple factors, including pCO2, explained the changes of BP, growth rate and Leu : TdR ratio at the end of the experiment. In contrast to BP, no clear trend and effect of changes of pCO2 was observed for BR, bacterial carbon demand and bacterial growth efficiency. Overall, the results suggest that changes in pCO2 potentially influence bacterial production, growth rate and growth balance rather than the conversion of dissolved organic matter into CO2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".