Evidence for a Temporary Positive Priming Effect in Aquatic Systems With Certain Substrates and Isotopic Discrimination of DOM Sources
Bibliographic record
Abstract
Abstract The “priming effect” (PE) is well documented in soils, but contradictory results have been reported in aquatic ecosystems. To investigate whether the presence of easily degradable labile dissolved organic matter (LDOM) changes the biodegradation rate of nonlabile DOM (NLDOM), incubations were performed with various sources of LDOM and NLDOM in microcosms amended with nutrients and a microbial inoculum. Stable carbon isotope analysis of DOM was used for the first time to estimate the PE. A significant positive PE (15%–34% of initial NLDOM) was measured, but only with mixed (glucose + amino acids) or complex (disaccharide) LDOM. Regardless of the LDOM, no PE was measured with more recalcitrant NLDOM (half‐life of 128 days here), when the LDOM/NLDOM ratio was low (0.3 versus 1), and when the NLDOM and microbial inoculum were from the same water (no mixing). The presence of sediments likely enhances microbial diversity and NLDOM degradation rate, but it did not increase the PE. Microbial use of LDOM produced new microbial NLDOM that should be discriminated (here by isotopes) from initial NLDOM for accurate PE measurements. The PE was temporary and lasted about 2 weeks after one LDOM addition. In areas with frequent additions of LDOM, a long‐lasting PE is expected and may significantly increase CO2 production. Exposing refractory DOM to new conditions and microbial community, such as during natural water mixing, seems to exert a strong control on its dynamics. Here, the addition of a new microbial inoculum had a stronger effect than adding LDOM or the PE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".